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 551–575 of 4891 papers

TitleStatusHype
Dropout Q-Functions for Doubly Efficient Reinforcement LearningCode1
DQO-MAP: Dual Quadrics Multi-Object mapping with Gaussian SplattingCode1
DualOpt: A Dual Divide-and-Optimize Algorithm for the Large-scale Traveling Salesman ProblemCode1
DynamicDet: A Unified Dynamic Architecture for Object DetectionCode1
DMM: Disparity-guided Multispectral Mamba for Oriented Object Detection in Remote SensingCode1
DiRe-JAX: A JAX based Dimensionality Reduction Algorithm for Large-scale DataCode1
DispFormer: Pretrained Transformer for Flexible Dispersion Curve Inversion from Global Synthesis to Regional ApplicationsCode1
Differentially Flat Learning-based Model Predictive Control Using a Stability, State, and Input Constraining Safety FilterCode1
Deep fiber clustering: Anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellationCode1
DiGRAF: Diffeomorphic Graph-Adaptive Activation FunctionCode1
A State-Space Perspective on Modelling and Inference for Online Skill RatingCode1
Delving into Masked Autoencoders for Multi-Label Thorax Disease ClassificationCode1
Detach-ROCKET: Sequential feature selection for time series classification with random convolutional kernelsCode1
Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object DetectionCode1
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation LearningCode1
DiMoSR: Feature Modulation via Multi-Branch Dilated Convolutions for Efficient Image Super-ResolutionCode1
A Survey of Mix-based Data Augmentation: Taxonomy, Methods, Applications, and ExplainabilityCode1
A Survey of World Models for Autonomous DrivingCode1
DragLoRA: Online Optimization of LoRA Adapters for Drag-based Image Editing in Diffusion ModelCode1
DnS: Distill-and-Select for Efficient and Accurate Video Indexing and RetrievalCode1
A Hybrid CNN-BiLSTM Voice Activity DetectorCode1
Dynamic Group Convolution for Accelerating Convolutional Neural NetworksCode1
DeepSeeColor: Realtime Adaptive Color Correction for Autonomous Underwater Vehicles via Deep Learning MethodsCode1
Deep reinforcement learning for large-scale epidemic controlCode1
Deep Speech Synthesis from MRI-Based Articulatory RepresentationsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified