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 1751–1775 of 4891 papers

TitleStatusHype
Comprehensive Survey of Model Compression and Speed up for Vision Transformers—0
Compositionally-Warped Gaussian Processes—0
Composite Marginal Likelihood Methods for Random Utility Models—0
Composite Gaussian Processes Flows for Learning Discontinuous Multimodal Policies—0
A Point-Based Approach to Efficient LiDAR Multi-Task Perception—0
Composite Event Recognition for Maritime Monitoring—0
Composing MPC with LQR and Neural Network for Amortized Efficiency and Stable Control—0
A Physics-informed machine learning model for time-dependent wave runup prediction—0
Advancing Semantic Caching for LLMs with Domain-Specific Embeddings and Synthetic Data—0
Advancing Physics Data Analysis through Machine Learning and Physics-Informed Neural Networks—0
Composable Cross-prompt Essay Scoring by Merging Models—0
A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations—0
Complexity-Driven CNN Compression for Resource-constrained Edge AI—0
A Pathway to Near Tissue Computing through Processing-in-CTIA Pixels for Biomedical Applications—0
Advancing Neuromorphic Computing: Mixed-Signal Design Techniques Leveraging Brain Code Units and Fundamental Code Units—0
Complementary Advantages: Exploiting Cross-Field Frequency Correlation for NIR-Assisted Image Denoising—0
A Path Integral Approach for Time-Dependent Hamiltonians with Applications to Derivatives Pricing—0
Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark—0
Comparative Study of Neural Network Methods for Solving Topological Solitons—0
A partial likelihood approach to tree-based density modeling and its application in Bayesian inference—0
Advancing Machine Learning in Industry 4.0: Benchmark Framework for Rare-event Prediction in Chemical Processes—0
A Comparison of Deep Learning Architectures for Spacecraft Anomaly Detection—0
Comparative Study of MPPT and Parameter Estimation of PV cells—0
Comparative Analysis of XGBoost and Minirocket Algortihms for Human Activity Recognition—0
A parsimonious, computationally efficient machine learning method for spatial regression—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified