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 3376–3400 of 4891 papers

TitleStatusHype
Data-driven reduced-order modelling for blood flow simulations with geometry-informed snapshotsCode0
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency—0
A comparative study of human inverse kinematics techniques for lower limbs—0
Non-separable Covariance Kernels for Spatiotemporal Gaussian Processes based on a Hybrid Spectral Method and the Harmonic Oscillator—0
Evaluation of Linear Implicit Quantized State System method for analyzing mission performance of power systems—0
A Novel Noise Injection-based Training Scheme for Better Model Robustness—0
Creating generalizable downstream graph models with random projections—0
A model-free feature selection technique of feature screening and random forest based recursive feature elimination—0
Fast and Blind Speech Copy-Move Detection and Localization in Noise—0
Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Model—0
Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution ShiftsCode0
The Framework Tax: Disparities Between Inference Efficiency in NLP Research and DeploymentCode0
Towards Fairer and More Efficient Federated Learning via Multidimensional Personalized Edge Models—0
Learning to Select Pivotal Samples for Meta Re-weightingCode0
On the Convergence of Modified Policy Iteration in Risk Sensitive Exponential Cost Markov Decision Processes—0
A Fast Bootstrap Algorithm for Causal Inference with Large DataCode0
Surrogate uncertainty estimation for your time series forecasting black-box: learn when to trust—0
Efficient End-to-End Video Question Answering with Pyramidal Multimodal TransformerCode0
Diffusion Models for High-Resolution Solar Forecasts—0
Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement LearningCode0
Skeleton-based Human Action Recognition via Convolutional Neural Networks (CNN)—0
A Modular Multi-stage Lightweight Graph Transformer Network for Human Pose and Shape Estimation from 2D Human Pose—0
Low-Carbon Economic Dispatch of Bulk Power Systems Using Nash Bargaining Game—0
Approximating DTW with a convolutional neural network on EEG data—0
Optimizing a Bayesian method for estimating the Hurst exponent in behavioral sciences—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified