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 801–825 of 4891 papers

TitleStatusHype
A few-shot Label Unlearning in Vertical Federated Learning—0
AFDetV2: Rethinking the Necessity of the Second Stage for Object Detection from Point Clouds—0
Spatial Attention-based Implicit Neural Representation for Arbitrary Reduction of MRI Slice Spacing—0
Perceptual Motor Learning with Active Inference Framework for Robust Lateral Control—0
A Fast Spectral Algorithm for Mean Estimation with Sub-Gaussian Rates—0
A Rank-SVM Approach to Anomaly Detection—0
A 3D grain-based reconstruction method from a 2D surface image for the Distinct Lattice Spring Model—0
Radiance Surfaces: Optimizing Surface Representations with a 5D Radiance Field Loss—0
A Question of Time: Revisiting the Use of Recursive Filtering for Temporal Calibration of Multisensor Systems—0
A Fast Effective Greedy Approach for MU-MIMO Beam Selection in mm-Wave and THz Communications—0
WaveMamba: Spatial-Spectral Wavelet Mamba for Hyperspectral Image Classification—0
Consensus-based Distributed Quantum Kernel Learning for Speech Recognition—0
A pseudo-likelihood approach to community detection in weighted networks—0
A Neuromorphic Proto-Object Based Dynamic Visual Saliency Model with an FPGA Implementation—0
A computational framework for optimal and Model Predictive Control of stochastic gene regulatory networks—0
PropEnc: A Property Encoder for Graph Neural Networks—0
A Fast Approximate AIB Algorithm for Distributional Word Clustering—0
Configurable Foundation Models: Building LLMs from a Modular Perspective—0
Conformal testing: binary case with Markov alternatives—0
8-bit Numerical Formats for Deep Neural Networks—0
A Predefined-Time Convergent and Noise-Tolerant Zeroing Neural Network Model for Time Variant Quadratic Programming With Application to Robot Motion Planning—0
A Comprehensive Survey on Deep Learning Solutions for 3D Flood Mapping—0
Conditional Expectation Propagation—0
Confidence-Aware Learning Optimal Terminal Guidance via Gaussian Process Regression—0
STC-ViT: Spatio Temporal Continuous Vision Transformer for Weather Forecasting—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified