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 991–1000 of 4891 papers

TitleStatusHype
Interweaving Insights: High-Order Feature Interaction for Fine-Grained Visual RecognitionCode0
Causal Customer Churn Analysis with Low-rank Tensor Block Hazard ModelCode0
ConSequence: Synthesizing Logically Constrained Sequences for Electronic Health Record GenerationCode0
Considerations in the use of ML interaction potentials for free energy calculationsCode0
A New Deep-learning-Based Approach For mRNA Optimization: High Fidelity, Computation Efficiency, and Multiple Optimization FactorsCode0
HAND: Hierarchical Attention Network for Multi-Scale Handwritten Document Recognition and Layout AnalysisCode0
Hamiltonian Monte Carlo Acceleration Using Surrogate Functions with Random BasesCode0
Hard constraint learning approaches with trainable influence functions for evolutionary equationsCode0
Can RLHF be More Efficient with Imperfect Reward Models? A Policy Coverage PerspectiveCode0
HADL Framework for Noise Resilient Long-Term Time Series ForecastingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified