Holistic Surgical Phase Recognition with Hierarchical Input Dependent State Space Models


SegMAN: Omni-scale Context Modeling with State Space Models and Local Attention for Semantic Segmentation


MambaVLT: Time-Evolving Multimodal State Space Model for Vision-Language Tracking


A Hybrid CNN-VSSM model for Multi-View, Multi-Task Mammography Analysis: Robust Diagnosis with Attention-Based Fusion


MambaADv2: Evolving Duality-enhanced State Space Model for Unsupervised Anomaly Detection


Gather-Scatter Mamba: Accelerating Propagation with Efficient State Space Model


Expressivity-Efficiency Tradeoffs for Hybrid Sequence Models


DA-Mamba: Learning Domain-Aware State Space Model for Global-Local Alignment in Domain Adaptive Object Detection


TSkel-Mamba: Temporal Dynamic Modeling via State Space Model for Human Skeleton-based Action Recognition


How Effective are State Space Models for Machine Translation?


Understanding and Enhancing Mamba-Transformer Hybrids for Memory Recall and Language Modeling


SasMamba: A Lightweight Structure-Aware Stride State Space Model for 3D Human Pose Estimation


Estimation of Corporate Greenhouse Gas Emissions via Machine Learning


Towards Sustainable SecureML: Quantifying Carbon Footprint of Adversarial Machine Learning


The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink


The Human Effect Requires Affect: Addressing Social-Psychological Factors of Climate Change with Machine Learning


Constructing artificial life and materials scientists with accelerated AI using Deep AndersoNN


Exploring the Carbon Footprint of Hugging Face's ML Models: A Repository Mining Study


LLMCO2: Advancing Accurate Carbon Footprint Prediction for LLM Inferences


EcoLearn: Optimizing the Carbon Footprint of Federated Learning


A first look into the carbon footprint of federated learning


Does Crypto Kill? Relationship between Electricity Consumption Carbon Footprints and Bitcoin Transactions


A User Study of Perceived Carbon Footprint


LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models


Carbon Footprint Reduction for Sustainable Data Centers in Real-Time


IoTCO2: Assessing the End-To-End Carbon Footprint of Internet-of-Things-Enabled Deep Learning


Carbon Footprint of Selecting and Training Deep Learning Models for Medical Image Analysis


Energy Usage Reports: Environmental awareness as part of algorithmic accountability


LLMSpace: Carbon Footprint Modeling for Large Language Model Inference on LEO Satellites


FTimeXer: Frequency-aware Time-series Transformer with Exogenous variables for Robust Carbon Footprint Forecasting


Improve Machine Learning carbon footprint using Nvidia GPU and Mixed Precision training for classification models -- Part I


Improve Machine Learning carbon footprint using Parquet dataset format and Mixed Precision training for regression models -- Part II


Power-Efficient Image Storage: Leveraging Super Resolution Generative Adversarial Network for Sustainable Compression and Reduced Carbon Footprint


Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning


Explainable automatic industrial carbon footprint estimation from bank transaction classification using natural language processing


Is TinyML Sustainable? Assessing the Environmental Impacts of Machine Learning on Microcontrollers


Counting Carbon: A Survey of Factors Influencing the Emissions of Machine Learning


Green Recommender Systems: Understanding and Minimizing the Carbon Footprint of AI-Powered Personalization


An Energy and Carbon Footprint Analysis of Distributed and Federated Learning


Towards Quantifying the Carbon Emissions of Differentially Private Machine Learning


Ground-Truthing AI Energy Consumption: Validating CodeCarbon Against External Measurements


Eco2AI: carbon emissions tracking of machine learning models as the first step towards sustainable AI


Datacenters in the Desert: Feasibility and Sustainability of LLM Inference in the Middle East


Accuracy and Consumption analysis from a compressed model by CompactifAI from Multiverse Computing


An Analysis of Optimizer Choice on Energy Efficiency and Performance in Neural Network Training


An Empirical Study of Sustainability in Prompt-driven Test Script Generation Using Small Language Models


WarpRec: Unifying Academic Rigor and Industrial Scale for Responsible, Reproducible, and Efficient Recommendation


DeCEAT: Decoding Carbon Emissions for AI-driven Software Testing


On the Carbon Footprint of Economic Research in the Age of Generative AI


Standardized Methods and Recommendations for Green Federated Learning


Towards eco friendly cybersecurity: machine learning based anomaly detection with carbon and energy metrics


Beyond Backpropagation: Exploring Innovative Algorithms for Energy-Efficient Deep Neural Network Training


Energy-Efficient Federated Learning via Adaptive Encoder Freezing for MRI-to-CT Conversion: A Green AI-Guided Research


Analog RF Computing: A New Paradigm for Energy-Efficient Edge AI Over MU-MIMO Systems


Fast and Energy-Efficient CNN Inference on IoT Devices


Active Inference Meeting Energy-Efficient Control of Parallel and Identical Machines


ECLIP: Energy-efficient and Practical Co-Location of ML Inference on Spatially Partitioned GPUs


Energy-Efficient Wireless LLM Inference via Uncertainty and Importance-Aware Speculative Decoding


Energy-Efficient Multimodal Inference Serving with Tri-serve


AutoScale: Optimizing Energy Efficiency of End-to-End Edge Inference under Stochastic Variance


E4: Energy-Efficient DNN Inference for Edge Video Analytics Via Early-Exit and DVFS


AdaOper: Energy-efficient and Responsive Concurrent DNN Inference on Mobile Devices


Energy-Efficient Edge Inference in Integrated Sensing, Communication, and Computation Networks


SparseDVFS: Sparse-Aware DVFS for Energy-Efficient Edge Inference


Energy-Efficient Dynamic Training and Inference for GNN-Based Network Modeling


Energy-Efficient Transformer Inference: Optimization Strategies for Time Series Classification


Hybrid-Parallel: Achieving High Performance and Energy Efficient Distributed Inference on Robots


A Converting Autoencoder Toward Low-latency and Energy-efficient DNN Inference at the Edge


Predictive Exit: Prediction of Fine-Grained Early Exits for Computation- and Energy-Efficient Inference


LLM-Guided Runtime Parameter Optimization for Energy-Efficient Model Inference


Energy-Efficient Inference Accelerator for Memory-Augmented Neural Networks on an FPGA


Energy-Efficient High-Accuracy Spiking Neural Network Inference Using Time-Domain Neurons


DTNN: Energy-efficient Inference with Dendrite Tree Inspired Neural Networks for Edge Vision Applications


HLSTransform: Energy-Efficient Llama 2 Inference on FPGAs Via High Level Synthesis


Towards Fast and Energy-Efficient Binarized Neural Network Inference on FPGA


EDEN: Enabling Energy-Efficient, High-Performance Deep Neural Network Inference Using Approximate DRAM


Energy-Efficient Processing and Robust Wireless Cooperative Transmission for Edge Inference


ETHEREAL: Energy-efficient and High-throughput Inference using Compressed Tsetlin Machine


Energy-Efficient Vision Transformer Inference for Edge-AI Deployment


Signatures of Bayesian inference emerge from energy efficient synapses


Dynamic Decision Tree Ensembles for Energy-Efficient Inference on IoT Edge Nodes


Energy-efficient neural network inference with microcavity exciton-polaritons


A Transistor Operations Model for Deep Learning Energy Consumption Scaling Law


Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training


Estimating Deep Learning energy consumption based on model architecture and training environment


A Deep Learning Approach for Macroscopic Energy Consumption Prediction with Microscopic Quality for Electric Vehicles


Deep Learning for Short-term Instant Energy Consumption Forecasting in the Manufacturing Sector


Can Adjusting Hyperparameters Lead to Green Deep Learning: An Empirical Study on Correlations between Hyperparameters and Energy Consumption of Deep Learning Models


Energy Consumption of Dataframe Libraries for End-to-End Deep Learning Pipelines:A Comparative Analysis


Explaining Deep Learning-based Anomaly Detection in Energy Consumption Data by Focusing on Contextually Relevant Data


Full-Cycle Energy Consumption Benchmark for Low-Carbon Computer Vision


Understanding the Energy Consumption of HPC Scale Artificial Intelligence


Extended vehicle energy dataset (eVED): an enhanced large-scale dataset for deep learning on vehicle trip energy consumption


Energy Consumption of Deep Generative Audio Models


NestDNN: Resource-Aware Multi-Tenant On-Device Deep Learning for Continuous Mobile Vision


EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search


RF-Photonic Deep Learning Processor with Shannon-Limited Data Movement


A Comparative Study on Energy Consumption Models for Drones


Energy Consumption Trends in Sound Event Detection Systems


Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads


Transfer Learning on Transformers for Building Energy Consumption Forecasting -- A Comparative Study


Towards energy-efficient Deep Learning: An overview of energy-efficient approaches along the Deep Learning Lifecycle


Deep Learning for Forecasting the Energy Consumption in Public Buildings


Forecasting Energy Consumption using Recurrent Neural Networks: A Comparative Analysis


Energy Consumption of Neural Networks on NVIDIA Edge Boards: an Empirical Model


Accuracy is not the only Metric that matters: Estimating the Energy Consumption of Deep Learning Models


Performance Analysis and Characterization of Training Deep Learning Models on Mobile Devices


From RNNs to Foundation Models: An Empirical Study on Commercial Building Energy Consumption


Watt For What: Rethinking Deep Learning's Energy-Performance Relationship


Measuring the Energy Consumption and Efficiency of Deep Neural Networks: An Empirical Analysis and Design Recommendations


Modelling the 5G Energy Consumption using Real-world Data: Energy Fingerprint is All You Need


Deep Ensemble Analysis for Imaging X-ray Polarimetry


Position: Tensor Networks are a Valuable Asset for Green AI


Energy-Efficient Green AI Architectures for Circular Economies Through Multi-Layered Sustainable Resource Optimization Framework


Uncovering Energy-Efficient Practices in Deep Learning Training: Preliminary Steps Towards Green AI


Benchmarking News Recommendation in the Era of Green AI


Green AI Carbon Optimizer: Carbon-Efficient Training Location Recommendation and Global AI Energy Demand Forecasting


How Do Companies Manage the Environmental Sustainability of AI? An Interview Study About Green AI Efforts and Regulations


Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation


NeuSpin: Design of a Reliable Edge Neuromorphic System Based on Spintronics for Green AI


Data-Centric Green AI: An Exploratory Empirical Study


Green AI in Action: Strategic Model Selection for Ensembles in Production


Advancing Green AI: Efficient and Accurate Lightweight CNNs for Rice Leaf Disease Identification


Towards green AI-based software systems: an architecture-centric approach (GAISSA)


TREE:Token-Responsive Energy Efficiency Framework For Green AI-Integrated 6G Networks


Intelligent Green Efficiency for Intrusion Detection


Efficient Explanations from Empirical Explainers


The More the Merrier? Navigating Accuracy vs. Energy Efficiency Design Trade-Offs in Ensemble Learning Systems


XAutoLM: Efficient Fine-Tuning of Language Models via Meta-Learning and AutoML


Training Green AI Models Using Elite Samples


Synergies between AI Computing and Power Systems: Metrics, Scheduling, and Resilience


Green-NAS: A Global-Scale Multi-Objective Neural Architecture Search for Robust and Efficient Edge-Native Weather Forecasting


Efficient Fine-Tuning Methods for Portuguese Question Answering: A Comparative Study of PEFT on BERTimbau and Exploratory Evaluation of Generative LLMs


Dissecting Transformers: A CLEAR Perspective towards Green AI


Batching for Green AI -- An Exploratory Study on Inference


Large Multimodal Model Compression via Efficient Pruning and Distillation at AntGroup


A Dataset Fusion Algorithm for Generalised Anomaly Detection in Homogeneous Periodic Time Series Datasets


MLPerf Power: Benchmarking the Energy Efficiency of Machine Learning Systems from Microwatts to Megawatts for Sustainable AI


Enabling more efficient and cost-effective AI/ML systems with Collective Mind, virtualized MLOps, MLPerf, Collective Knowledge Playground and reproducible optimization tournaments


AdvScan: Black-Box Adversarial Example Detection at Runtime through Power Analysis


Multi-Complexity-Loss DNAS for Energy-Efficient and Memory-Constrained Deep Neural Networks


AIPerf: Automated machine learning as an AI-HPC benchmark


High performance and energy efficient inference for deep learning on ARM processors


Enhancing Neural Architecture Search with Multiple Hardware Constraints for Deep Learning Model Deployment on Tiny IoT Devices


UniFusion: Unified Multi-view Fusion Transformer for Spatial-Temporal Representation in Bird's-Eye-View


FusionFormer: A Multi-sensory Fusion in Bird's-Eye-View and Temporal Consistent Transformer for 3D Object Detection


Cross-Dataset Experimental Study of Radar-Camera Fusion in Bird's-Eye View


Post Fusion Bird's Eye View Feature Stabilization for Robust Multimodal 3D Detection


CoBEVFusion: Cooperative Perception with LiDAR-Camera Bird's-Eye View Fusion


Evaluation of an Uncertainty-Aware Late Fusion Algorithm for Multi-Source Bird's Eye View Detections Under Controlled Noise


BEVFusion4D: Learning LiDAR-Camera Fusion Under Bird's-Eye-View via Cross-Modality Guidance and Temporal Aggregation


NeMO: Neural Map Growing System for Spatiotemporal Fusion in Bird's-Eye-View and BDD-Map Benchmark


Fisheye Camera and Ultrasonic Sensor Fusion For Near-Field Obstacle Perception in Bird's-Eye-View


FIERY: Future Instance Prediction in Bird's-Eye View from Surround Monocular Cameras


BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation


BroadBEV: Collaborative LiDAR-camera Fusion for Broad-sighted Bird's Eye View Map Construction


RC-BEVFusion: A Plug-In Module for Radar-Camera Bird's Eye View Feature Fusion


MIC-BEV: Multi-Infrastructure Camera Bird's-Eye-View Transformer with Relation-Aware Fusion for 3D Object Detection


BEV-DG: Cross-Modal Learning under Bird's-Eye View for Domain Generalization of 3D Semantic Segmentation


Learning Content-Aware Multi-Modal Joint Input Pruning via Bird's-Eye-View Representation


LaRa: Latents and Rays for Multi-Camera Bird's-Eye-View Semantic Segmentation


EarlyBird: Early-Fusion for Multi-View Tracking in the Bird's Eye View


Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipe


IS-Fusion: Instance-Scene Collaborative Fusion for Multimodal 3D Object Detection


BEVCooper: Accurate and Communication-Efficient Bird's-Eye-View Perception in Vehicular Networks


A Resource Efficient Fusion Network for Object Detection in Bird's-Eye View using Camera and Raw Radar Data


AVM-SLAM: Semantic Visual SLAM with Multi-Sensor Fusion in a Bird's Eye View for Automated Valet Parking


DuoSpaceNet: Leveraging Both Bird's-Eye-View and Perspective View Representations for 3D Object Detection


X-Align++: cross-modal cross-view alignment for Bird's-eye-view segmentation


OnlineBEV: Recurrent Temporal Fusion in Bird's Eye View Representations for Multi-Camera 3D Perception


X-Align: Cross-Modal Cross-View Alignment for Bird's-Eye-View Segmentation


Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data


Unauthorized Drone Detection: Experiments and Prototypes


Real-Time Drone Detection and Tracking With Visible, Thermal and Acoustic Sensors


Track Boosting and Synthetic Data Aided Drone Detection


RIS-Augmented Millimeter-Wave MIMO Systems for Passive Drone Detection


VBSF-TLD: Validation-Based Approach for Soft Computing-Inspired Transfer Learning in Drone Detection


Robust Low-Cost Drone Detection and Classification in Low SNR Environments


ODD-SEC: Onboard Drone Detection with a Spinning Event Camera


SynDroneVision: A Synthetic Dataset for Image-Based Drone Detection


Neuromorphic Drone Detection: an Event-RGB Multimodal Approach


Introduction to Drone Detection Radar with Emphasis on Automatic Target Recognition (ATR) technology


LRDDv2: Enhanced Long-Range Drone Detection Dataset with Range Information and Comprehensive Real-World Challenges


YOLO-FEDER FusionNet: A Novel Deep Learning Architecture for Drone Detection


Lightweight Multi-Drone Detection and 3D-Localization via YOLO


A dataset for multi-sensor drone detection


Enabling Drone Detection with SWARM Repeater-Assisted MIMO ISAC


YOLOMG: Vision-based Drone-to-Drone Detection with Appearance and Pixel-Level Motion Fusion


Cell-free ISAC for Drone Detection Considering Coverage and Age of Sensing


Designing an Objective-Driven Test Method for the Comparative Performance Evaluation of Commercial DTI Solutions for Counter UAS systems


CubeDN: Real-time Drone Detection in 3D Space from Dual mmWave Radar Cubes


YOLOBirDrone: Dataset for Bird vs Drone Detection and Classification and a YOLO based enhanced learning architecture


Towards a High-Performance Object Detector: Insights from Drone Detection Using ViT and CNN-based Deep Learning Models


LRDDv3: High-Resolution Long-Range Drone Detection Dataset with Range Information and Thermal Data


Rogue Drone Detection: A Machine Learning Approach


DroBoost: An Intelligent Score and Model Boosting Method for Drone Detection


TransVisDrone: Spatio-Temporal Transformer for Vision-based Drone-to-Drone Detection in Aerial Videos


Drone Detection and Tracking with YOLO and a Rule-based Method


3DifFusionDet: Diffusion Model for 3D Object Detection with Robust LiDAR-Camera Fusion


TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers


SupFusion: Supervised LiDAR-Camera Fusion for 3D Object Detection


FGFusion: Fine-Grained Lidar-Camera Fusion for 3D Object Detection


Exploring Adversarial Robustness of LiDAR-Camera Fusion Model in Autonomous Driving


Improving Robustness of LiDAR-Camera Fusion Model against Weather Corruption from Fusion Strategy Perspective


BadFusion: 2D-Oriented Backdoor Attacks against 3D Object Detection


InsFusion: Rethink Instance-level LiDAR-Camera Fusion for 3D Object Detection


Multi-View Adaptive Fusion Network for 3D Object Detection


Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous Driving


VoxelNextFusion: A Simple, Unified and Effective Voxel Fusion Framework for Multi-Modal 3D Object Detection


Detecting As Labeling: Rethinking LiDAR-camera Fusion in 3D Object Detection


SparseLIF: High-Performance Sparse LiDAR-Camera Fusion for 3D Object Detection


LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusion


Adaptive LiDAR Scanning: Harnessing Temporal Cues for Efficient 3D Object Detection via Multi-Modal Fusion


FusionRCNN: LiDAR-Camera Fusion for Two-stage 3D Object Detection


An Efficient LiDAR-Camera Fusion Network for Multi-Class 3D Dynamic Object Detection and Trajectory Prediction


SimDistill: Simulated Multi-modal Distillation for BEV 3D Object Detection


LDRFusion: A LiDAR-Dominant multimodal refinement framework for 3D object detection


Multi-level and multi-modal feature fusion for accurate 3D object detection in Connected and Automated Vehicles


MultiCorrupt: A Multi-Modal Robustness Dataset and Benchmark of LiDAR-Camera Fusion for 3D Object Detection


Enhancing Pseudo-Boxes via Data-Level LiDAR-Camera Fusion for Unsupervised 3D Object Detection


MLF-4DRCNet: Multi-Level Fusion with 4D Radar and Camera for 3D Object Detection in Autonomous Driving


AdaptiveShape: Solving Shape Variability for 3D Object Detection with Geometry Aware Anchor Distributions


Comparative survey: People detection, tracking and multi-sensor Fusion in a video sequence


MSF3DDETR: Multi-Sensor Fusion 3D Detection Transformer for Autonomous Driving


DAOcc: 3D Object Detection Assisted Multi-Sensor Fusion for 3D Occupancy Prediction


UniMSF: A Unified Multi-Sensor Fusion Framework for Intelligent Transportation System Global Localization


Adaptive Quantized Planetary Crater Detection System for Autonomous Space Exploration


Multi-view and Multi-modal Event Detection Utilizing Transformer-based Multi-sensor fusion


DifFUSER: Diffusion Model for Robust Multi-Sensor Fusion in 3D Object Detection and BEV Segmentation


Detecting Multi-Sensor Fusion Errors in Advanced Driver-Assistance Systems


ContextualFusion: Context-Based Multi-Sensor Fusion for 3D Object Detection in Adverse Operating Conditions


Minimizing Occlusion Effect on Multi-View Camera Perception in BEV with Multi-Sensor Fusion


COMMIT: Certifying Robustness of Multi-Sensor Fusion Systems against Semantic Attacks


NavEYE: Vision-Centered Multi-Sensor Fusion-Based Situational Awareness System for Intelligent Surface Vehicles


A Multi-Sensor Fusion Parking Barrier System with Lightweight Vision on Edge


MultiTest: Physical-Aware Object Insertion for Testing Multi-sensor Fusion Perception Systems


An Intelligent Water-Saving Irrigation System Based on Multi-Sensor Fusion and Visual Servoing Control


Cross-Modal Phantom: Coordinated Camera-LiDAR Spoofing Against Multi-Sensor Fusion in Autonomous Vehicles


Benchmarking Robustness of AI-Enabled Multi-sensor Fusion Systems: Challenges and Opportunities


A Survey of Multi-sensor Fusion Perception for Embodied AI: Background, Methods, Challenges and Prospects


Intelligent Multimodal Multi-Sensor Fusion-Based UAV Identification, Localization, and Countermeasures for Safeguarding Low-Altitude Economy


Testing the Fault-Tolerance of Multi-Sensor Fusion Perception in Autonomous Driving Systems


Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks


Multi-Task Multi-Sensor Fusion for 3D Object Detection


CurbScan: Curb Detection and Tracking Using Multi-Sensor Fusion


Proactive Anomaly Detection for Robot Navigation with Multi-Sensor Fusion


Real-Time Roadway Obstacle Detection for Electric Scooters Using Deep Learning and Multi-Sensor Fusion


Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties


Obstacle Detection at Level Crossings under Adverse Weather Conditions -- A Survey


Group Equivariant BEV for 3D Object Detection


RCBEVDet++: Toward High-accuracy Radar-Camera Fusion 3D Perception Network


Radar Camera Fusion via Representation Learning in Autonomous Driving


Enhanced Radar Perception via Multi-Task Learning: Towards Refined Data for Sensor Fusion Applications


Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review


calibfusion: Transformer-Based Differentiable Calibration for Radar-Camera Fusion Detection in Water-Surface Environments


Horizon3D: Sparse Radar-Camera Fusion for Long-Range 3D Perception in Autonomous Driving


WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmarks for Autonomous Driving on Water Surfaces


CFTrack: Center-based Radar and Camera Fusion for 3D Multi-Object Tracking


RaCFormer: Towards High-Quality 3D Object Detection via Query-based Radar-Camera Fusion


HGSFusion: Radar-Camera Fusion with Hybrid Generation and Synchronization for 3D Object Detection


Sparse4D-Radar: An Efficient and Robust Framework for Surround-View 3D Object Detection via 4D Radar-Camera Fusion


MSSF: A 4D Radar and Camera Fusion Framework With Multi-Stage Sampling for 3D Object Detection in Autonomous Driving


Camera-Radar Perception for Autonomous Vehicles and ADAS: Concepts, Datasets and Metrics


Radar-Camera BEV Multi-Task Learning with Cross-Task Attention Bridge for Joint 3D Detection and Segmentation


Revisiting Radar Camera Alignment by Contrastive Learning for 3D Object Detection


RadSegNet: A Reliable Approach to Radar Camera Fusion


Radar-Camera Sensor Fusion for Joint Object Detection and Distance Estimation in Autonomous Vehicles


SpaRC: Sparse Radar-Camera Fusion for 3D Object Detection


Instance-Guided Radar Depth Estimation for 3D Object Detection


LRC-WeatherNet: LiDAR, RADAR, and Camera Fusion Network for Real-time Weather-type Classification in Autonomous Driving


Boosting Instance Awareness via Cross-View Correlation with 4D Radar and Camera for 3D Object Detection


DinoRADE: Full Spectral Radar-Camera Fusion with Vision Foundation Model Features for Multi-class Object Detection in Adverse Weather


Boosting Online 3D Multi-Object Tracking through Camera-Radar Cross Check


SpaRC-AD: A Baseline for Radar-Camera Fusion in End-to-End Autonomous Driving


MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources


Radar-Informed 3D Multi-Object Tracking under Adverse Conditions


EagerMOT: 3D Multi-Object Tracking via Sensor Fusion


Decentralised Variational Inference Frameworks for Multi-object Tracking on Sensor Networks: Additional Notes


ShaSTA-Fuse: Camera-LiDAR Sensor Fusion to Model Shape and Spatio-Temporal Affinities for 3D Multi-Object Tracking


DFR-FastMOT: Detection Failure Resistant Tracker for Fast Multi-Object Tracking Based on Sensor Fusion


Graph-Based Multi-Modal Sensor Fusion for Autonomous Driving


Towards Multi-Object-Tracking with Radar on a Fast Moving Vehicle: On the Potential of Processing Radar in the Frequency Domain


Toward a Union-Find decoder for quantum LDPC codes


Beam search decoder for quantum LDPC codes


Cluster Decomposition for Improved Erasure Decoding of Quantum LDPC Codes


Online Gaussian elimination for quantum LDPC decoding


Improved Quantum LDPC Decoding Strategies For The Misidentified Quantum Depolarizing Channel


Stabilizer Inactivation for Message-Passing Decoding of Quantum LDPC Codes


Erasure Decoding for Quantum LDPC Codes via Belief Propagation with Guided Decimation


A Scalable FPGA Architecture for Real-Time Decoding of Quantum LDPC Codes Using GARI


Power and Limitations of Linear Programming Decoder for Quantum LDPC Codes


Graph Neural Networks for Enhanced Decoding of Quantum LDPC Codes


Decoding Correlated Errors in Quantum LDPC Codes


Decoding Across the Quantum LDPC Code Landscape


Decodable quantum LDPC codes beyond the $\sqrt{n}$ distance barrier using high dimensional expanders


Fully Parallelized BP Decoding for Quantum LDPC Codes Can Outperform BP-OSD


Viderman's algorithm for quantum LDPC codes


Channel Identification and its Impact on Quantum LDPC Code Performance


Quantum LDPC Codes Constructed from Point-Line Subsets of the Finite Projective Plane


Breaking the Orthogonality Barrier in Quantum LDPC Codes


Quaternary Neural Belief Propagation Decoding of Quantum LDPC Codes with Overcomplete Check Matrices


Breaking the bicycle frame: Coset-based quantum LDPC codes


Random Construction of Quantum LDPC Codes


Degenerate Quantum LDPC Codes With Good Finite Length Performance


Golden codes: quantum LDPC codes built from regular tessellations of hyperbolic 4-manifolds


A Class of Quantum LDPC Codes Constructed From Finite Geometries


Fast erasure decoder for hypergraph product codes


Restart Belief: A General Quantum LDPC Decoder


The closed-branch decoder for quantum LDPC codes


An efficient decoder for a linear distance quantum LDPC code


Automorphism Ensemble Decoding of Quantum LDPC Codes


Benchmarking Machine Learning Models for Quantum Error Correction


Machine Learning for Continuous Quantum Error Correction on Superconducting Qubits


Quantum Error Correction and Detection for Quantum Machine Learning


Quantum Error Correction with Quantum Autoencoders


Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correction


Optimizing continuous-time quantum error correction for arbitrary noise


Quantum Global Variational Learning for Quantum Error Correction


Efficient and Universal Neural-Network Decoder for Stabilizer-Based Quantum Error Correction


Optimizing Quantum Error Correction Codes with Reinforcement Learning


Machine learning logical gates for quantum error correction


QVECTOR: an algorithm for device-tailored quantum error correction


Fooling the Decoder: An Adversarial Attack on Quantum Error Correction


Discovering autonomous quantum error correction via deep reinforcement learning


Design Automation in Quantum Error Correction


Generative Decoding for Quantum Error-correcting Codes


Decoherence and Quantum Error Correction for Quantum Computing and Communications


Transformer-QEC: Quantum Error Correction Code Decoding with Transferable Transformers


Scalable Neural Decoders for Practical Real-Time Quantum Error Correction


Artificial Intelligence for Quantum Error Correction: A Comprehensive Review


Transmon qubit readout fidelity at the threshold for quantum error correction without a quantum-limited amplifier


Rethink the Role of Neural Decoders in Quantum Error Correction


Maximum Likelihood Decoding of Quantum Error Correction Codes


Machine Learning for Quantum Noise Reduction


Learning Logical Operations for Arbitrary Quantum Error Correction Codes


A Cryogenic Memristive Neural Decoder for Fault-tolerant Quantum Error Correction


Bayesian Optimization for Quantum Error-Correcting Code Discovery


Machine-learning based three-qubit gate for realization of a Toffoli gate with cQED-based transmon systems


Neural-Network Decoders for Quantum Error Correction using Surface Codes:A Space Exploration of the Hardware Cost-Performance Trade-Offs


Neural network decoder confidence as a learned proxy for the logical gap


Learning to Decode in Parallel: Self-Coordinating Neural Network for Real-Time Quantum Error Correction


Importance sampling for data-driven decoding of quantum error-correcting codes


Machine-learning-assisted correction of correlated qubit errors in a topological code


Decoding Small Surface Codes with Feedforward Neural Networks


HyperNQ: A Hypergraph Neural Network Decoder for Quantum LDPC Codes


On the interpretability of neural network decoders


Machine Learning Optimal Quantum Error Correction Thresholds


Learning Neural Decoding with Parallelism and Self-Coordination for Quantum Error Correction


Real-time Surface-Code Error Correction Using an FPGA-based Neural-Network Decoder


Scalable Neural Network Decoders for Higher Dimensional Quantum Codes


Scalable Neural Decoders for Practical Fault-Tolerant Quantum Computation


Fully convolutional 3D neural network decoders for surface codes with syndrome circuit noise


Improved error correction with leakage reduction units built into qubit measurement in a superconducting quantum processor


Probing and Enhancing the Robustness of GNN-based QEC Decoders with Reinforcement Learning


Surface code logical operations on a superconducting quantum processor


Subsystem many-hypercube codes: High-rate concatenated codes with low-weight syndrome measurements


Decoding quantum error correction with Ising model hardware


Real-Time Decoding for Fault-Tolerant Quantum Computing: Progress, Challenges and Outlook


Real-Time Quantum Error Correction System Stack: Architecture, Algorithms, and Engineering Practice


Demonstrating real-time and low-latency quantum error correction with superconducting qubits


LILLIPUT: A Lightweight Low-Latency Lookup-Table Based Decoder for Near-term Quantum Error Correction


Promatch: Extending the Reach of Real-Time Quantum Error Correction with Adaptive Predecoding


Calibration-Conditioned FiLM Decoders for Low-Latency Decoding of Quantum Error Correction Evaluated on IBM Repetition-Code Experiments


Quantum error correction below the surface code threshold


Decoder Switching: Breaking the Speed-Accuracy Tradeoff in Real-Time Quantum Error Correction


Mitigating Classical Resource Costs in Quantum Error Correction via Generalized qLDPC Predecoding


Soft information decoding with superconducting qubits


Testing the Accuracy of Surface Code Decoders


Realization of real-time fault-tolerant quantum error correction


High-performance cellular automaton decoders for quantum repetition and toric code


Improved Belief Propagation Decoding Algorithms for Surface Codes


Correcting a noisy quantum computer using a quantum computer


Network-Integrated Decoding System for Real-Time Quantum Error Correction with Lattice Surgery


Enhancing Fault-Tolerant Surface Code Decoding with Iterative Lattice Reweighting


Colour Codes Reach Surface Code Performance using Vibe Decoding


A Scalable, Fast and Programmable Neural Decoder for Fault-Tolerant Quantum Computation Using Surface Codes


Spatially parallel decoding for multi-qubit lattice surgery


LATTE: A Decoding Architecture for Quantum Computing with Temporal and Spatial Scalability


Efficient Post-Selection for General Quantum LDPC Codes


LEGO: QEC Decoding System Architecture for Dynamic Circuits


Neural network decoder for near-term surface-code experiments


Minimising surface-code failures using a color-code decoder


Decoding across transversal Clifford gates in the surface code


Decoding surface code with a distributed neural network based decoder


A Symmetry-Integrated Approach to Surface Code Decoding


A scalable and fast artificial neural network syndrome decoder for surface codes


Linear-time general decoding algorithm for the surface code


A fast fault-tolerant decoder for qubit and qudit surface codes


Qubit-centric Transformer for Surface Code Decoding


Scalable surface code decoders with parallelization in time


Optimal adaptation of surface-code decoders to local noise


Improved decoding of circuit noise and fragile boundaries of tailored surface codes


Efficient soft-output decoders for the surface code


Machine Learning Decoding of Circuit-Level Noise for Bivariate Bicycle Codes


Performance enhancement of surface codes via recursive MWPM decoding


Phases of decodability in the surface code with unitary errors


Learning to Decode the Surface Code with a Recurrent, Transformer-Based Neural Network


High-Level Surface Code Decoding via Parallel FFNNs on CIM Platforms


Efficient Algorithms for Maximum Likelihood Decoding in the Surface Code


Efficient Decoding of Surface Code Syndromes for Error Correction in Quantum Computing


Hardness results for decoding the surface code with Pauli noise


Spanning Tree Matching Decoder for Quantum Surface Codes


Tailoring surface codes for highly biased noise


Information-efficient decoding of surface codes


Improved accuracy for decoding surface codes with matching synthesis


SAQ: Stabilizer-Aware Quantum Error Correction Decoder


HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face


MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework


Generative Agents: Interactive Simulacra of Human Behavior


Voyager: An Open-Ended Embodied Agent with Large Language Models


Graph of Thoughts: Solving Elaborate Problems with Large Language Models


Tree of Thoughts: Deliberate Problem Solving with Large Language Models


GAIA: a benchmark for General AI Assistants


Toolformer: Language Models Can Teach Themselves to Use Tools


Reflexion: Language Agents with Verbal Reinforcement Learning


Self-Refine: Iterative Refinement with Self-Feedback


MemGPT: Towards LLMs as Operating Systems


Beyond static AI evaluations (agentic) / A-Mem agentic memory


Carbon Emissions and Large Neural Network Training


Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training


Power Hungry Processing: Watts Driving the Cost of AI Deployment?


Deep Neural Network Probabilistic Decoder for Stabilizer Codes


Reinforcement Learning Decoders for Fault-Tolerant Quantum Computation


Learning high-accuracy error decoding for quantum processors (AlphaQubit)


PyMatching: A Python package for decoding quantum codes with MWPM


Stim: a fast stabilizer circuit simulator


Neural network decoders for quantum error correcting codes


nuScenes: A multimodal dataset for autonomous driving


The KITTI Vision Benchmark / sensor fusion


Scalability in Perception for Autonomous Driving: Waymo Open Dataset


VINS-Fusion / robust visual-inertial state estimation


Hymba: A Hybrid-head Architecture for Small Language Models


Samba: Simple Hybrid State Space Models for Efficient Unlimited Context


ML.ENERGY Initiative (SymbioticLab, Michigan)