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 4051–4075 of 4891 papers

TitleStatusHype
Efficient Semantic Diffusion Architectures for Model Training on Synthetic EchocardiogramsCode0
Sparse Ellipsoidal Radial Basis Function Network for Point Cloud Surface RepresentationCode0
Efficient Segmentation: Learning Downsampling Near Semantic BoundariesCode0
Sparse Estimation with the Swept Approximated Message-Passing AlgorithmCode0
Efficient Robust Conformal Prediction via Lipschitz-Bounded NetworksCode0
Offline RL with Smooth OOD Generalization in Convex Hull and its NeighborhoodCode0
Adaptive Spiral Layers for Efficient 3D Representation Learning on MeshesCode0
DeepHGCN: Toward Deeper Hyperbolic Graph Convolutional NetworksCode0
Resilient Set-based State Estimation for Linear Time-Invariant Systems Using ZonotopesCode0
Implicit Regularization for Optimal Sparse RecoveryCode0
Sparse Gaussian Process Variational AutoencodersCode0
BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic ProgrammingCode0
OML-AD: Online Machine Learning for Anomaly Detection in Time Series DataCode0
Improving Variational Auto-Encoders using Householder FlowCode0
CFIR: Fast and Effective Long-Text To Image Retrieval for Large CorporaCode0
Efficient Quantification and Representation of Aggregate Flexibility in Electric VehiclesCode0
Implicit Generative Prior for Bayesian Neural NetworksCode0
Incorporating brain-inspired mechanisms for multimodal learning in artificial intelligenceCode0
Sparse Implementation of Versatile Graph-Informed LayersCode0
Sparse L0-norm based Kernel-free Quadratic Surface Support Vector MachinesCode0
DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging DataCode0
A Survey on Large-scale Machine LearningCode0
Onboard Satellite Image Classification for Earth Observation: A Comparative Study of ViT ModelsCode0
AdaAnn: Adaptive Annealing Scheduler for Probability Density ApproximationCode0
Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory NetworksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified