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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1326–1350 of 4891 papers

TitleStatusHype
FREEtree: A Tree-based Approach for High Dimensional Longitudinal Data With Correlated FeaturesCode0
Deep-learning the Latent Space of Light TransportCode0
A tensor network approach for chaotic time series predictionCode0
Reachability Analysis Using Constrained Polynomial Logical ZonotopesCode0
FORTRESS: Function-composition Optimized Real-Time Resilient Structural Segmentation via Kolmogorov-Arnold Enhanced Spatial Attention NetworksCode0
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture DesignCode0
A Temporal Linear Network for Time Series ForecastingCode0
FlowKac: An Efficient Neural Fokker-Planck solver using Temporal Normalizing flows and the Feynman Kac-FormulaCode0
Interweaving Insights: High-Order Feature Interaction for Fine-Grained Visual RecognitionCode0
Flow Annealed Importance Sampling Bootstrap meets Differentiable Particle PhysicsCode0
Adaptive Action Duration with Contextual Bandits for Deep Reinforcement Learning in Dynamic EnvironmentsCode0
Missing Data Imputation Based on Dynamically Adaptable Structural Equation Modeling with Self-AttentionCode0
Iterative Distributed Multinomial RegressionCode0
From Roots to Rewards: Dynamic Tree Reasoning with RLCode0
Iterative Semi-Supervised Learning for Abdominal Organs and Tumor SegmentationCode0
Generalized Population-Based Training for Hyperparameter Optimization in Reinforcement LearningCode0
Deep Learning for Early Alzheimer Disease Detection with MRI ScansCode0
Deep Learning Evidence for Global Optimality of Gerver's SofaCode0
A Targeted Accuracy Diagnostic for Variational ApproximationsCode0
KernelDNA: Dynamic Kernel Sharing via Decoupled Naive AdaptersCode0
Kernel Heterogeneity Improves Sparseness of Natural Images RepresentationsCode0
Deep Coarse-to-fine Dense Light Field Reconstruction with Flexible Sampling and Geometry-aware FusionCode0
Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep LearningCode0
Flexible Robust Optimal Bidding of Renewable Virtual Power Plants in Sequential MarketsCode0
Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse HypergraphsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified