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 521–530 of 4891 papers

TitleStatusHype
Efficient and Information-Preserving Future Frame Prediction and BeyondCode1
DiRe-JAX: A JAX based Dimensionality Reduction Algorithm for Large-scale DataCode1
DiMoSR: Feature Modulation via Multi-Branch Dilated Convolutions for Efficient Image Super-ResolutionCode1
Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object DetectionCode1
Differentially Flat Learning-based Model Predictive Control Using a Stability, State, and Input Constraining Safety FilterCode1
Deep fiber clustering: Anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellationCode1
DiGRAF: Diffeomorphic Graph-Adaptive Activation FunctionCode1
DispFormer: Pretrained Transformer for Flexible Dispersion Curve Inversion from Global Synthesis to Regional ApplicationsCode1
DeformUX-Net: Exploring a 3D Foundation Backbone for Medical Image Segmentation with Depthwise Deformable ConvolutionCode1
AIM 2024 Challenge on UHD Blind Photo Quality AssessmentCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified