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 3576–3600 of 4891 papers

TitleStatusHype
Composing MPC with LQR and Neural Network for Amortized Efficiency and Stable Control—0
Stacked Generative Machine Learning Models for Fast Approximations of Steady-State Navier-Stokes Equations—0
LSTM-based model predictive control with discrete inputs for irrigation scheduling—0
A Sparse Expansion For Deep Gaussian Processes—0
ST-MTL: Spatio-Temporal Multitask Learning Model to Predict Scanpath While Tracking Instruments in Robotic SurgeryCode0
DeepRLS: A Recurrent Network Architecture with Least Squares Implicit Layers for Non-blind Image Deconvolution—0
Fast Point TransformerCode1
Dynamic Flow Equilibrium of Transportation and Power Distribution Networks Considering Flexible Traveling Choices and Voltage Quality Improvement—0
Learnable Faster Kernel-PCA for Nonlinear Fault Detection: Deep Autoencoder-Based Realization—0
γ-Net: Superresolving SAR Tomographic Inversion via Deep Learning—0
Fully Attentional Network for Semantic SegmentationCode1
SHRIMP: Sparser Random Feature Models via Iterative Magnitude PruningCode0
Self-Organized Polynomial-Time Coordination GraphsCode0
Universalizing Weak Supervision—0
Self-Supervised Camera Self-Calibration from Video—0
Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Vision—0
Is Class-Incremental Enough for Continual Learning?—0
U2-Former: A Nested U-shaped Transformer for Image Restoration—0
Multi-scale Graph Convolutional Networks with Self-Attention—0
MT-TransUNet: Mediating Multi-Task Tokens in Transformers for Skin Lesion Segmentation and ClassificationCode1
Temporally Resolution Decrement: Utilizing the Shape Consistency for Higher Computational Efficiency—0
CondenseNeXt: An Ultra-Efficient Deep Neural Network for Embedded SystemsCode0
Shallow Network Based on Depthwise Over-Parameterized Convolution for Hyperspectral Image Classification—0
SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity MeasurementCode0
Hyperbolic Procrustes Analysis Using Riemannian GeometryCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified