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 1376–1400 of 4891 papers

TitleStatusHype
Flexible Robust Optimal Bidding of Renewable Virtual Power Plants in Sequential MarketsCode0
FlowKac: An Efficient Neural Fokker-Planck solver using Temporal Normalizing flows and the Feynman Kac-FormulaCode0
Free Parametrization of L2-bounded State Space ModelsCode0
Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep LearningCode0
DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging DataCode0
FinNet: Solving Time-Independent Differential Equations with Finite Difference Neural NetworkCode0
Deep convolutional recurrent autoencoders for learning low-dimensional feature dynamics of fluid systemsCode0
Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse HypergraphsCode0
Fast and Accurate Amplitude Demodulation of Wideband SignalsCode0
DSSRNN: Decomposition-Enhanced State-Space Recurrent Neural Network for Time-Series AnalysisCode0
LightPure: Realtime Adversarial Image Purification for Mobile Devices Using Diffusion ModelsCode0
First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient NoiseCode0
Deep convolutional neural network for shape optimization using level-set approachCode0
Linear Algorithms for Robust and Scalable Nonparametric Multiclass Probability EstimationCode0
Efficient State Space Model via Fast Tensor Convolution and Block DiagonalizationCode0
Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous mediaCode0
Deep autoregressive neural networks for high-dimensional inverse problems in groundwater contaminant source identificationCode0
Finding Influential Training Samples for Gradient Boosted Decision TreesCode0
FGP: Feature-Gradient-Prune for Efficient Convolutional Layer PruningCode0
A Hybrid Framework for Reinsurance Optimization: Integrating Generative Models and Reinforcement LearningCode0
Fighting Randomness with Randomness: Mitigating Optimisation Instability of Fine-Tuning using Delayed Ensemble and Noisy InterpolationCode0
A Survey on Prompt TuningCode0
Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement LearningCode0
Filtered Markovian Projection: Dimensionality Reduction in Filtering for Stochastic Reaction NetworksCode0
FREEtree: A Tree-based Approach for High Dimensional Longitudinal Data With Correlated FeaturesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified