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 3676–3700 of 4891 papers

TitleStatusHype
MugenNet: A Novel Combined Convolution Neural Network and Transformer Network with its Application for Colonic Polyp Image Segmentation—0
Multi-Agent Motion Planning using Deep Learning for Space Applications—0
Multi-Agent Reinforcement Learning with Selective State-Space Models—0
Multi-Channel CNN-based Object Detection for Enhanced Situation Awareness—0
Multi-feature classifiers for burst detection in single EEG channels from preterm infants—0
Multi-Fidelity Bayesian Neural Network for Uncertainty Quantification in Transonic Aerodynamic Loads—0
Multifidelity Cross-validation—0
Multifidelity Ensemble Kalman Filtering Using Surrogate Models Defined by Physics-Informed Autoencoders—0
Multi-Fidelity Methods for Optimization: A Survey—0
Multi-fidelity surrogate with heterogeneous input spaces for modeling melt pools in laser-directed energy deposition—0
Multi-frequency calibration for DOA estimation with distributed sensors—0
Multi-frequency Neural Born Iterative Method for Solving 2-D Inverse Scattering Problems—0
Multi-frequency wavefield solutions for variable velocity models using meta-learning enhanced low-rank physics-informed neural network—0
Multi-Grained Feature Pruning for Video-Based Human Pose Estimation—0
Multi-grained Trajectory Graph Convolutional Networks for Habit-unrelated Human Motion Prediction—0
Multi-language Video Subtitle Dataset for Image-based Text Recognition—0
Explainable Gated Bayesian Recurrent Neural Network for Non-Markov State Estimation—0
Multilevel Monte Carlo For Exponential L\'evy Models—0
Multilevel Monte Carlo in Sample Average Approximation: Convergence, Complexity and Application—0
Multi-Level Monte Carlo Training of Neural Operators—0
Multilingual De-Duplication Strategies: Applying scalable similarity search with monolingual & multilingual embedding models—0
Multimodal Deep Learning for Low-Resource Settings: A Vector Embedding Alignment Approach for Healthcare Applications—0
Multi-Modal Financial Time-Series Retrieval Through Latent Space Projections—0
Multimodal Fused Learning for Solving the Generalized Traveling Salesman Problem in Robotic Task Planning—0
Multimodal Fusion Balancing Through Game-Theoretic Regularization—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified