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

Showing 44014425 of 4891 papers

TitleStatusHype
Linear Transformers as VAR Models: Aligning Autoregressive Attention Mechanisms with Autoregressive ForecastingCode0
ST-MTL: Spatio-Temporal Multitask Learning Model to Predict Scanpath While Tracking Instruments in Robotic SurgeryCode0
Continuous vs. Discrete Optimization of Deep Neural NetworksCode0
Uni-Encoder: A Fast and Accurate Response Selection Paradigm for Generation-Based Dialogue SystemsCode0
Toward Reliable AR-Guided Surgical Navigation: Interactive Deformation Modeling with Data-Driven Biomechanics and PromptsCode0
Lite-FBCN: Lightweight Fast Bilinear Convolutional Network for Brain Disease Classification from MRI ImageCode0
LiteSeg: A Novel Lightweight ConvNet for Semantic SegmentationCode0
A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret PerformanceCode0
Global Safe Sequential Learning via Efficient Knowledge TransferCode0
DynaMMo: Dynamic Model Merging for Efficient Class Incremental Learning for Medical ImagesCode0
PET Tracer Separation Using Conditional Diffusion Transformer with Multi-latent Space LearningCode0
GFSNetwork: Differentiable Feature Selection via Gumbel-Sigmoid RelaxationCode0
Stochastic Conjugate Gradient Algorithm with Variance ReductionCode0
Adaptive Data Exploitation in Deep Reinforcement LearningCode0
Stochastic filtering for multiscale stochastic reaction networks based on hybrid approximationsCode0
Geoseg: A Computer Vision Package for Automatic Building Segmentation and Outline ExtractionCode0
Continual Learning Through Synaptic IntelligenceCode0
LMBiS-Net: A Lightweight Multipath Bidirectional Skip Connection based CNN for Retinal Blood Vessel SegmentationCode0
Scalable Bayesian Rule ListsCode0
PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst DesignCode0
Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry DetectionCode0
Supervised Dimensionality Reduction for Big DataCode0
Stochastic Gradient Descent without Full Data ShuffleCode0
Tight lower bounds for Dynamic Time WarpingCode0
A general framework for supporting economic feasibility of generator and storage energy systems through capacity and dispatch optimizationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified