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 1481–1490 of 4891 papers

TitleStatusHype
HC^3L-Diff: Hybrid conditional latent diffusion with high frequency enhancement for CBCT-to-CT synthesis—0
Quantum Rationale-Aware Graph Contrastive Learning for Jet Discrimination—0
Federated Learning with Relative Fairness—0
Cross-D Conv: Cross-Dimensional Transferable Knowledge Base via Fourier Shifting OperationCode0
WaKA: Data Attribution using K-Nearest Neighbors and Membership Privacy Principles—0
An Efficient Hierarchical Preconditioner-Learner Architecture for Reconstructing Multi-scale Basis Functions of High-dimensional Subsurface Fluid Flow—0
SANN-PSZ: Spatially Adaptive Neural Network for Head-Tracked Personal Sound Zones—0
Modern, Efficient, and Differentiable Transport Equation Models using JAX: Applications to Population Balance Equations—0
Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-OptimizationCode2
3D Equivariant Pose Regression via Direct Wigner-D Harmonics Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified