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

Showing 13211330 of 4891 papers

TitleStatusHype
Dis-S2V: Discourse Informed Sen2VecCode0
Dissecting FLOPs along input dimensions for GreenAI cost estimationsCode0
FlowKac: An Efficient Neural Fokker-Planck solver using Temporal Normalizing flows and the Feynman Kac-FormulaCode0
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture DesignCode0
Flover: A Temporal Fusion Framework for Efficient Autoregressive Model Parallel InferenceCode0
Distance Metric Learning for Graph Structured DataCode0
A Temporal Linear Network for Time Series ForecastingCode0
Flow Annealed Importance Sampling Bootstrap meets Differentiable Particle PhysicsCode0
Flexible Robust Optimal Bidding of Renewable Virtual Power Plants in Sequential MarketsCode0
GCSAM: Gradient Centralized Sharpness Aware MinimizationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified