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 2526–2550 of 4891 papers

TitleStatusHype
Re-initialization-free Level Set Method via Molecular Beam Epitaxy Equation Regularization for Image Segmentation—0
REJEPA: A Novel Joint-Embedding Predictive Architecture for Efficient Remote Sensing Image Retrieval—0
Relative-Translation Invariant Wasserstein Distance—0
Relaxation-Free Min-k-Partition for PCI Assignment in 5G Networks—0
Reliability Analysis of Complex Multi-State System Based on Universal Generating Function and Bayesian Network—0
Reliability Analysis of Complex Systems using Subset Simulations with Hamiltonian Neural Networks—0
Reliable and superior elliptic Fourier descriptor normalization and its application software ElliShape with efficient image processing—0
Reliable Feature Selection for Adversarially Robust Cyber-Attack Detection—0
Reliable Solution to Dynamic Optimization Problems using Integrated Residual Regularized Direct Collocation—0
Rel-UNet: Reliable Tumor Segmentation via Uncertainty Quantification in nnU-Net—0
ReLU Surrogates in Mixed-Integer MPC for Irrigation Scheduling—0
Remember and Recall: Associative-Memory-based Trajectory Prediction—0
RemInD: Remembering Anatomical Variations for Interpretable Domain Adaptive Medical Image Segmentation—0
RemoteDet-Mamba: A Hybrid Mamba-CNN Network for Multi-modal Object Detection in Remote Sensing Images—0
Representation Meets Optimization: Training PINNs and PIKANs for Gray-Box Discovery in Systems Pharmacology—0
Representing Flow Fields with Divergence-Free Kernels for Reconstruction—0
Reproducibility Evaluation of SLANT Whole Brain Segmentation Across Clinical Magnetic Resonance Imaging Protocols—0
RepSNet: A Nucleus Instance Segmentation model based on Boundary Regression and Structural Re-parameterization—0
Research Advances and New Paradigms for Biology-inspired Spiking Neural Networks—0
Research on Cloud Platform Network Traffic Monitoring and Anomaly Detection System based on Large Language Models—0
Research on Edge Detection of LiDAR Images Based on Artificial Intelligence Technology—0
Research on feature fusion and multimodal patent text based on graph attention network—0
Reservoir Computing Models for Patient-Adaptable ECG Monitoring in Wearable Devices—0
Residual Attention Single-Head Vision Transformer Network for Rolling Bearing Fault Diagnosis in Noisy Environments—0
Residual-based Attention Physics-informed Neural Networks for Spatio-Temporal Ageing Assessment of Transformers Operated in Renewable Power Plants—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified