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 3326–3350 of 4891 papers

TitleStatusHype
Multitask Learning via Shared Features: Algorithms and Hardness—0
Tube-Based Zonotopic Data-Driven Predictive ControlCode1
Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training—0
Optimistic Optimization of Gaussian Process Samples—0
Latent Similarity Identifies Important Functional Connections for Phenotype PredictionCode0
A Consistent ICM-based χ^2 Specification Test—0
Inferring subhalo effective density slopes from strong lensing observations with neural likelihood-ratio estimationCode0
Improving the Efficiency of Gradient Descent Algorithms Applied to Optimization Problems with Dynamical Constraints—0
Complexity-Driven CNN Compression for Resource-constrained Edge AI—0
Algorithmic Differentiation for Automated Modeling of Machine Learned Force FieldsCode1
Multi-Resolution Subspace-Based Optimization Method for the Retrieval of 2D Perfect Electric Conductors—0
Algorithms of Real-Time Navigation and Control of Autonomous Unmanned Vehicles—0
Towards Efficient Capsule NetworksCode0
Curbing Task Interference using Representation Similarity-Guided Multi-Task Feature SharingCode0
Learning-based estimation of in-situ wind speed from underwater acoustics—0
Regression modelling of spatiotemporal extreme U.S. wildfires via partially-interpretable neural networksCode0
ARES: An Efficient Algorithm with Recurrent Evaluation and Sampling-Driven Inference for Maximum Independent Set—0
Convolutional Spiking Neural Networks for Detecting Anticipatory Brain Potentials Using Electroencephalogram—0
An Algorithm-Hardware Co-Optimized Framework for Accelerating N:M Sparse Transformers—0
Automating DBSCAN via Deep Reinforcement LearningCode1
An Unconstrained Symmetric Nonnegative Latent Factor Analysis for Large-scale Undirected Weighted Networks—0
Simplified State Space Layers for Sequence ModelingCode2
Human Activity Recognition Using Cascaded Dual Attention CNN and Bi-Directional GRU Framework—0
Are Gradients on Graph Structure Reliable in Gray-box Attacks?Code0
On Fast Simulation of Dynamical System with Neural Vector Enhanced Numerical SolverCode1
Show:102550
← PrevPage 134 of 196Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified