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 3426–3450 of 4891 papers

TitleStatusHype
Tool flank wear prediction using high-frequency machine data from industrial edge device—0
Enhanced prediction accuracy with uncertainty quantification in monitoring CO2 sequestration using convolutional neural networks—0
STLGRU: Spatio-Temporal Lightweight Graph GRU for Traffic Flow PredictionCode0
Learning to Optimize in Model Predictive Control—0
Graph Convolutional Neural Networks with Diverse Negative Samples via Decomposed Determinant Point ProcessesCode0
Regularized ERM on random subspaces—0
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping—0
Robust and Fast Measure of Information via Low-rank RepresentationCode0
Safe and Efficient Reinforcement Learning Using Disturbance-Observer-Based Control Barrier Functions—0
xTrimoABFold: De novo Antibody Structure Prediction without MSA—0
Towards More Robust Interpretation via Local Gradient AlignmentCode0
Machine Learning Accelerated PDE Backstepping Observers—0
Condensed Gradient BoostingCode0
Mutual Guidance and Residual Integration for Image Enhancement—0
Fingerprint Image-Quality Estimation and its Application to Multialgorithm Verification—0
SimVPv2: Towards Simple yet Powerful Spatiotemporal Predictive Learning—0
MSS-DepthNet: Depth Prediction with Multi-Step Spiking Neural Network—0
PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst DesignCode0
Enhancing Mobile Robot Navigation Safety and Efficiency through NMPC with Relaxed CBF in Dynamic Environments—0
Spatio-temporal point processes with deep non-stationary kernels—0
Beyond Attentive Tokens: Incorporating Token Importance and Diversity for Efficient Vision TransformersCode0
Real-time Local Feature with Global Visual Information Enhancement—0
A Transformer Framework for Data Fusion and Multi-Task Learning in Smart CitiesCode0
Brain Inspired Cortical Coding Method for Fast Clustering and Codebook Generation—0
Molecular Fingerprints for Robust and Efficient ML-Driven Molecular Generation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified