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 3941–3950 of 4891 papers

TitleStatusHype
RMP2: A Structured Composable Policy Class for Robot Learning—0
Analytically Tractable Inference in Deep Neural Networks—0
Loosely Synchronized Search for Multi-agent Path Finding with Asynchronous Actions—0
HTMD-Net: A Hybrid Masking-Denoising Approach to Time-Domain Monaural Singing Voice Separation—0
Accumulations of Projections--A Unified Framework for Random Sketches in Kernel Ridge Regression—0
Joint Network Topology Inference via Structured Fusion Regularization—0
Eigen-spectrograms: An interpretable feature space for bearing fault diagnosis based on artificial intelligence and image processing—0
Variance Reduced Median-of-Means Estimator for Byzantine-Robust Distributed Inference—0
Anharmonic Raman spectra simulation of crystals from deep neural networks—0
ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified