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 2061–2070 of 4891 papers

TitleStatusHype
An algorithm for two-player repeated games with imperfect public monitoringCode0
Quantum Rationale-Aware Graph Contrastive Learning for Jet Discrimination—0
Federated Learning with Relative Fairness—0
WaKA: Data Attribution using K-Nearest Neighbors and Membership Privacy Principles—0
Cross-D Conv: Cross-Dimensional Transferable Knowledge Base via Fourier Shifting OperationCode0
SANN-PSZ: Spatially Adaptive Neural Network for Head-Tracked Personal Sound Zones—0
3D Equivariant Pose Regression via Direct Wigner-D Harmonics Prediction—0
An Efficient Hierarchical Preconditioner-Learner Architecture for Reconstructing Multi-scale Basis Functions of High-dimensional Subsurface Fluid Flow—0
Modern, Efficient, and Differentiable Transport Equation Models using JAX: Applications to Population Balance Equations—0
ψDAG: Projected Stochastic Approximation Iteration for DAG Structure LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified