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 4001–4025 of 4891 papers

TitleStatusHype
Episodic Memory for Learning Subjective-Timescale Models—0
A computationally efficient reconstruction algorithm for circular cone-beam computed tomography using shallow neural networks—0
Self-grouping Convolutional Neural NetworksCode1
Multi-Relational Embedding for Knowledge Graph Representation and AnalysisCode1
A Survey on Deep Learning Methods for Semantic Image Segmentation in Real-Time—0
Towards a Systematic Computational Framework for Modeling Multi-Agent Decision-Making at Micro Level for Smart Vehicles in a Smart World—0
Event-Driven Receding Horizon Control for Distributed Estimation in Network Systems—0
Bandit Change-Point Detection for Real-Time Monitoring High-Dimensional Data Under Sampling Control—0
Self-Weighted Robust LDA for Multiclass Classification with Edge Classes—0
A Derivative-free Method for Quantum Perceptron Training in Multi-layered Neural Networks—0
Region Growing with Convolutional Neural Networks for Biomedical Image Segmentation—0
Multiscale Context-Aware Ensemble Deep KELM for Efficient Hyperspectral Image ClassificationCode1
PP-OCR: A Practical Ultra Lightweight OCR SystemCode2
Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based ModelsCode0
Overlapping community detection in networks via sparse spectral decompositionCode0
Improving Spiking Sparse Recovery via Non-Convex Penalties—0
Event-based update of synapses in voltage-based learning rules—0
Empirical Fourier Decomposition: An Accurate Adaptive Signal Decomposition Method—0
Multi^2OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERTCode1
A computationally efficient physiologically comprehensive 3D-0D closed-loop model of the heart and circulation—0
Accurate and efficient Simulation of very high-dimensional Neural Mass Models with distributed-delay Connectome Tensors—0
Collaborative Group Learning—0
MATS: An Interpretable Trajectory Forecasting Representation for Planning and ControlCode1
Fixed Inducing Points Online Bayesian Calibration for Computer Models with an Application to a Scale-Resolving CFD Simulation—0
Extracting Optimal Solution Manifolds using Constrained Neural Optimization—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified