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 4261–4270 of 4891 papers

TitleStatusHype
Scale-Equivariant Steerable NetworksCode0
Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation—0
Accelerated Structured Alternating Projections for Robust Spectrally Sparse Signal RecoveryCode0
Commonsense Knowledge Base Completion with Structural and Semantic ContextCode0
Neural Multisensory Scene InferenceCode0
Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and MappingCode1
Covariance-free Partial Least Squares: An Incremental Dimensionality Reduction MethodCode0
Multiagent Rollout Algorithms and Reinforcement LearningCode0
Integrated Triaging for Fast Reading Comprehension—0
Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural NetworksCode0
Show:102550
← PrevPage 427 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified