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

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Showing 1291–1300 of 4891 papers

TitleStatusHype
FORTRESS: Function-composition Optimized Real-Time Resilient Structural Segmentation via Kolmogorov-Arnold Enhanced Spatial Attention NetworksCode0
A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical SystemsCode0
Reachability Analysis Using Constrained Polynomial Logical ZonotopesCode0
Fovea Transformer: Efficient Long-Context Modeling with Structured Fine-to-Coarse AttentionCode0
ATLAS: Adapting Trajectory Lengths and Step-Size for Hamiltonian Monte CarloCode0
Flow Annealed Importance Sampling Bootstrap meets Differentiable Particle PhysicsCode0
Deep neural networks with controlled variable selection for the identification of putative causal genetic variantsCode0
Dimension-reduced Optimization of Multi-zone Thermostatically Controlled LoadsCode0
Active ML for 6G: Towards Efficient Data Generation, Acquisition, and AnnotationCode0
Flexible Robust Optimal Bidding of Renewable Virtual Power Plants in Sequential MarketsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified