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 1401–1450 of 4891 papers

TitleStatusHype
Missing Data Imputation Based on Dynamically Adaptable Structural Equation Modeling with Self-AttentionCode0
DualView: Data Attribution from the Dual PerspectiveCode0
Fovea Transformer: Efficient Long-Context Modeling with Structured Fine-to-Coarse AttentionCode0
Reachability Analysis Using Constrained Polynomial Logical ZonotopesCode0
FORTRESS: Function-composition Optimized Real-Time Resilient Structural Segmentation via Kolmogorov-Arnold Enhanced Spatial Attention NetworksCode0
FrameRS: A Video Frame Compression Model Composed by Self supervised Video Frame Reconstructor and Key Frame SelectorCode0
DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging DataCode0
Deep convolutional recurrent autoencoders for learning low-dimensional feature dynamics of fluid systemsCode0
Free Parametrization of L2-bounded State Space ModelsCode0
Deep convolutional neural network for shape optimization using level-set approachCode0
Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous mediaCode0
QE-BEV: Query Evolution for Bird's Eye View Object Detection in Varied ContextsCode0
Dynamic Bi-Elman Attention Networks: A Dual-Directional Context-Aware Test-Time Learning for Text ClassificationCode0
Flover: A Temporal Fusion Framework for Efficient Autoregressive Model Parallel InferenceCode0
Deep autoregressive neural networks for high-dimensional inverse problems in groundwater contaminant source identificationCode0
Flow Annealed Importance Sampling Bootstrap meets Differentiable Particle PhysicsCode0
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture DesignCode0
Deep Coarse-to-fine Dense Light Field Reconstruction with Flexible Sampling and Geometry-aware FusionCode0
A Hybrid Framework for Reinsurance Optimization: Integrating Generative Models and Reinforcement LearningCode0
Flexible Robust Optimal Bidding of Renewable Virtual Power Plants in Sequential MarketsCode0
A Survey on Prompt TuningCode0
FlowKac: An Efficient Neural Fokker-Planck solver using Temporal Normalizing flows and the Feynman Kac-FormulaCode0
FREEtree: A Tree-based Approach for High Dimensional Longitudinal Data With Correlated FeaturesCode0
GCNv2: Efficient Correspondence Prediction for Real-Time SLAMCode0
Graph Neural Networks for modelling breast biomechanical compressionCode0
Improving Hyper-Relational Knowledge Graph CompletionCode0
A Survey on Large-scale Machine LearningCode0
First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient NoiseCode0
Decomposing the Time Series Forecasting Pipeline: A Modular Approach for Time Series Representation, Information Extraction, and ProjectionCode0
A Cascaded Dilated Convolution Approach for Mpox Lesion ClassificationCode0
Decomposing and Fusing Intra- and Inter-Sensor Spatio-Temporal Signal for Multi-Sensor Wearable Human Activity RecognitionCode0
DecomCAM: Advancing Beyond Saliency Maps through Decomposition and IntegrationCode0
FinNet: Solving Time-Independent Differential Equations with Finite Difference Neural NetworkCode0
Dynamics-aware Adversarial Attack of Adaptive Neural NetworksCode0
An algorithm for two-player repeated games with imperfect public monitoringCode0
Decentralized and Lifelong-Adaptive Multi-Agent Collaborative LearningCode0
Debiasing Evidence Approximations: On Importance-weighted Autoencoders and Jackknife Variational InferenceCode0
Finding Influential Training Samples for Gradient Boosted Decision TreesCode0
DeBaCl: A Python Package for Interactive DEnsity-BAsed CLusteringCode0
DCR: Quantifying Data Contamination in LLMs EvaluationCode0
Action Recognition Using Temporal Shift Module and Ensemble LearningCode0
Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse HypergraphsCode0
Feed-Forward Optimization With Delayed Feedback for Neural NetworksCode0
Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement LearningCode0
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNsCode0
FGP: Feature-Gradient-Prune for Efficient Convolutional Layer PruningCode0
Federated Learning for Time-Series Healthcare Sensing with Incomplete ModalitiesCode0
DBgDel: Database-Enhanced Gene Deletion Framework for Growth-Coupled Production in Genome-Scale Metabolic ModelsCode0
Federated Learning with Reservoir State Analysis for Time Series Anomaly DetectionCode0
Data-to-Model Distillation: Data-Efficient Learning FrameworkCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified