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 3026–3050 of 4891 papers

TitleStatusHype
Posterior Sampling for Deep Reinforcement LearningCode1
Beyond Prediction: On-street Parking Recommendation using Heterogeneous Graph-based List-wise RankingCode0
Physics-Guided Graph Neural Networks for Real-time AC/DC Power Flow Analysis—0
Learning battery model parameter dynamics from data with recursive Gaussian process regression—0
Feed-Forward Optimization With Delayed Feedback for Neural NetworksCode0
Towards Compute-Optimal Transfer Learning—0
Alternating Local Enumeration (TnALE): Solving Tensor Network Structure Search with Fewer EvaluationsCode0
Centrality-Based Node Feature Augmentation for Robust Network Alignment—0
Optimal Design of Neural Network Structure for Power System Frequency Security Constraints—0
A hierarchical adaptive nonlinear model predictive control approach for maximizing tire force usage in autonomous vehicles—0
Gradient-Descent Based Optimization of Multi-Tone Sinusoidal Frequency Modulated Waveforms—0
Two Birds, One Stone: A Unified Framework for Joint Learning of Image and Video Style TransfersCode1
SSN: Stockwell Scattering Network for SAR Image Change Detection—0
WATT-EffNet: A Lightweight and Accurate Model for Classifying Aerial Disaster ImagesCode0
OptoGPT: A Foundation Model for Inverse Design in Optical Multilayer Thin Film Structures—0
Probabilistic Forecast-based Portfolio Optimization of Electricity Demand at Low Aggregation Levels—0
Detection and Classification of Glioblastoma Brain Tumor—0
Improving Autoregressive NLP Tasks via Modular Linearized Attention—0
Reconfigurable Intelligent Surface-Enabled Gridless DoA Estimation System for NLoS Scenarios—0
Comparative Study of MPPT and Parameter Estimation of PV cells—0
FedBlockHealth: A Synergistic Approach to Privacy and Security in IoT-Enabled Healthcare through Federated Learning and Blockchain—0
An Interpretable Approach to Load Profile Forecasting in Power Grids using Galerkin-Approximated Koopman PseudospectraCode0
Learning in latent spaces improves the predictive accuracy of deep neural operatorsCode1
A Machine Learning-Enhanced Benders Decomposition Approach to Solve the Transmission Expansion Planning Problem under Uncertainty—0
Model Predictive Control with Self-supervised Representation LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified