SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2651–2675 of 4891 papers

TitleStatusHype
Multi-view learning for automatic classification of multi-wavelength auroral images—0
Riemannian Laplace Approximation with the Fisher MetricCode0
Mixed Models with Multiple Instance LearningCode1
Successor Features for Efficient Multisubject Controlled Text Generation—0
TCM-GPT: Efficient Pre-training of Large Language Models for Domain Adaptation in Traditional Chinese Medicine—0
Efficient Neural Ranking using Forward Indexes and Lightweight Encoders—0
Learning Collective Behaviors from Observation—0
Electronic excited states from physically-constrained machine learning—0
Bandit-Driven Batch Selection for Robust Learning under Label Noise—0
YOLOv8-Based Visual Detection of Road Hazards: Potholes, Sewer Covers, and Manholes—0
Interpretable Neural PDE Solvers using Symbolic Frameworks—0
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation—0
Video Frame Interpolation with Many-to-many Splatting and Spatial Selective Refinement—0
Triplet Attention Transformer for Spatiotemporal Predictive Learning—0
Optimization-Free Test-Time Adaptation for Cross-Person Activity RecognitionCode1
Med-DANet V2: A Flexible Dynamic Architecture for Efficient Medical Volumetric Segmentation—0
Lookup Table meets Local Laplacian Filter: Pyramid Reconstruction Network for Tone MappingCode1
Image Prior and Posterior Conditional Probability Representation for Efficient Damage Assessment—0
Orchestration of Emulator Assisted Mobile Edge Tuning for AI Foundation Models: A Multi-Agent Deep Reinforcement Learning Approach—0
Efficient safe learning for controller tuning with experimental validation—0
Proactive Emergency Collision Avoidance for Automated Driving in Highway Scenarios—0
Explainable Gated Bayesian Recurrent Neural Network for Non-Markov State Estimation—0
Model Input-Output Configuration Search with Embedded Feature Selection for Sensor Time-series and Image ClassificationCode0
Stochastic Gradient Sampling for Enhancing Neural Networks Training—0
Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian InferenceCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified