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 3201–3250 of 4891 papers

TitleStatusHype
Enhanced prediction accuracy with uncertainty quantification in monitoring CO2 sequestration using convolutional neural networks—0
STLGRU: Spatio-Temporal Lightweight Graph GRU for Traffic Flow PredictionCode0
HADAS: Hardware-Aware Dynamic Neural Architecture Search for Edge Performance ScalingCode1
Graph Convolutional Neural Networks with Diverse Negative Samples via Decomposed Determinant Point ProcessesCode0
SoftCTC -- Semi-Supervised Learning for Text Recognition using Soft Pseudo-LabelsCode1
Learning to Optimize in Model Predictive Control—0
Regularized ERM on random subspaces—0
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping—0
Robust and Fast Measure of Information via Low-rank RepresentationCode0
Safe and Efficient Reinforcement Learning Using Disturbance-Observer-Based Control Barrier Functions—0
xTrimoABFold: De novo Antibody Structure Prediction without MSA—0
Lie Group Forced Variational Integrator Networks for Learning and Control of Robot SystemsCode1
Towards More Robust Interpretation via Local Gradient AlignmentCode0
Machine Learning Accelerated PDE Backstepping Observers—0
Fast-SNARF: A Fast Deformer for Articulated Neural FieldsCode2
Condensed Gradient BoostingCode0
Mutual Guidance and Residual Integration for Image Enhancement—0
Spatial-Spectral Transformer for Hyperspectral Image DenoisingCode1
Fingerprint Image-Quality Estimation and its Application to Multialgorithm Verification—0
MECCH: Metapath Context Convolution-based Heterogeneous Graph Neural NetworksCode1
PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst DesignCode0
SimVPv2: Towards Simple yet Powerful Spatiotemporal Predictive Learning—0
MSS-DepthNet: Depth Prediction with Multi-Step Spiking Neural Network—0
Beyond Attentive Tokens: Incorporating Token Importance and Diversity for Efficient Vision TransformersCode0
Enhancing Mobile Robot Navigation Safety and Efficiency through NMPC with Relaxed CBF in Dynamic Environments—0
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