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 3351–3375 of 4891 papers

TitleStatusHype
Graph Regularized Nonnegative Latent Factor Analysis Model for Temporal Link Prediction in Cryptocurrency Transaction Networks—0
Robust Graph Neural Networks using Weighted Graph LaplacianCode0
A Screening Strategy for Structured Optimization Involving Nonconvex _q,p Regularization—0
Accelerated and interpretable oblique random survival forestsCode1
A Real-time Edge-AI System for Reef Surveys—0
Neural Architecture Search on Efficient Transformers and Beyond—0
Distributed Differential Dynamic Programming Architectures for Large-Scale Multi-Agent Control—0
Integrating Statistical and Machine Learning Approaches to Identify Receptive Field Structure in Neural Populations—0
TransCL: Transformer Makes Strong and Flexible Compressive LearningCode1
Statistical and Computational Trade-offs in Variational Inference: A Case Study in Inferential Model Selection—0
Fast Data Driven Estimation of Cluster Number in Multiplex Images using Embedded Density Outliers—0
Generalized Analysis and Unified Design of EM Skins—0
SepLUT: Separable Image-adaptive Lookup Tables for Real-time Image EnhancementCode1
BIP: Boost Invariant Polynomials for Efficient Jet TaggingCode0
Defect Transformer: An Efficient Hybrid Transformer Architecture for Surface Defect Detection—0
Multiscale Causal Structure Learning—0
Action Recognition With Motion Diversification and Dynamic Selection—0
STRIKE-GOLDD 4.0: user-friendly, efficient analysis of structural identifiability and observabilityCode1
Continual Learning For On-Device Environmental Sound ClassificationCode1
Equivariant Hypergraph Diffusion Neural OperatorsCode1
AdamNODEs: When Neural ODE Meets Adaptive Moment EstimationCode0
PointNorm: Dual Normalization is All You Need for Point Cloud AnalysisCode1
Safe Drone Flight with Time-Varying Backup Controllers—0
Numerical Comparisons of Linear Power Flow Approximations: Optimality, Feasibility, and Computation Time—0
DeepSNR: A deep learning foundation for offline gravitational wave detection—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified