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 3226–3250 of 4891 papers

TitleStatusHype
Spatio-temporal point processes with deep non-stationary kernels—0
Real-time Local Feature with Global Visual Information Enhancement—0
A Transformer Framework for Data Fusion and Multi-Task Learning in Smart CitiesCode0
Brain Inspired Cortical Coding Method for Fast Clustering and Codebook Generation—0
Statistical Inference for Coadded Astronomical ImagesCode1
Molecular Fingerprints for Robust and Efficient ML-Driven Molecular Generation—0
Resilient Set-based State Estimation for Linear Time-Invariant Systems Using ZonotopesCode0
Selectively Linearized Neural Network based RoCoF-Constrained Unit Commitment in Low-Inertia Power Systems—0
Model Predictive Control for Signal Temporal Logic Specifications with Time Interval DecompositionCode1
A Survey on the Integration of Machine Learning with Sampling-based Motion Planning—0
Edge2Vec: A High Quality Embedding for the Jigsaw Puzzle Problem—0
Evaluating Distribution System Reliability with Hyperstructures Graph Convolutional Nets—0
Zero-shot Image Captioning by Anchor-augmented Vision-Language Space Alignment—0
Structured Singular Value of a Repeated Complex Full-Block Uncertainty—0
Soft-Landing Strategy for Alleviating the Task Discrepancy Problem in Temporal Action Localization TasksCode0
Robust DNN Surrogate Models with Uncertainty Quantification via Adversarial Training—0
Robust N-1 secure HV Grid Flexibility Estimation for TSO-DSO coordinated Congestion Management with Deep Reinforcement Learning—0
Efficient Large-scale Audio Tagging via Transformer-to-CNN Knowledge DistillationCode2
Truthful Transaction Protocol for E-Commerce Networks Based on Double Auction—0
A kinetic approach to consensus-based segmentation of biomedical images—0
Active Learning with Tabular Language Models—0
A Neural Network Subgrid Model of the Early Stages of Planet Formation—0
Learning From Alarms: A Robust Learning Approach for Accurate Photoplethysmography-Based Atrial Fibrillation Detection using Eight Million Samples Labeled with Imprecise Arrhythmia AlarmsCode1
A Filtering-based General Approach to Learning Rational Constraints of Epistemic Graphs—0
Fast Quasi-Optimal Power Flow of Flexible DC Traction Power Systems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified