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 3076–3100 of 4891 papers

TitleStatusHype
EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level LatenciesCode2
Marching-Primitives: Shape Abstraction from Signed Distance FunctionCode1
NVAutoNet: Fast and Accurate 360^ 3D Visual Perception For Self Driving—0
Revisiting DeepFool: generalization and improvementCode0
Hardness of Independent Learning and Sparse Equilibrium Computation in Markov Games—0
A Novel and Optimal Spectral Method for Permutation Synchronization—0
GNN-Assisted Phase Space Integration with Application to Atomistics—0
Optimized preprocessing and Tiny ML for Attention State Classification—0
SIESTA: Efficient Online Continual Learning with SleepCode1
FD-Net: An Unsupervised Deep Forward-Distortion Model for Susceptibility Artifact Correction in EPICode0
XVoxel-Based Parametric Design Optimization of Feature Models—0
A Spatio-temporal Decomposition Method for the Coordinated Economic Dispatch of Integrated Transmission and Distribution Grids—0
HDformer: A Higher Dimensional Transformer for Diabetes Detection Utilizing Long Range Vascular Signals—0
Robust Mode Connectivity-Oriented Adversarial Defense: Enhancing Neural Network Robustness Against Diversified _p AttacksCode1
All4One: Symbiotic Neighbour Contrastive Learning via Self-Attention and Redundancy ReductionCode0
Active Semi-Supervised Learning by Exploring Per-Sample Uncertainty and Consistency—0
BiFormer: Vision Transformer with Bi-Level Routing AttentionCode2
Interpretable Ensembles of Hyper-Rectangles as Base ModelsCode0
Optimal Sampling Designs for Multi-dimensional Streaming Time Series with Application to Power Grid Sensor Data—0
Gradient-Descent Based Optimization of Constant Envelope OFDM Waveforms—0
Dynamic Clustering and Cluster Contrastive Learning for Unsupervised Person Re-identificationCode1
Importance Filtering with Risk Models for Complex Driving Situations—0
NeurEPDiff: Neural Operators to Predict Geodesics in Deformation Spaces—0
BCSSN: Bi-direction Compact Spatial Separable Network for Collision Avoidance in Autonomous Driving—0
A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph DataCode4
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified