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 3301–3350 of 4891 papers

TitleStatusHype
OptoGPT: A Foundation Model for Inverse Design in Optical Multilayer Thin Film Structures—0
Detection and Classification of Glioblastoma Brain Tumor—0
Probabilistic Forecast-based Portfolio Optimization of Electricity Demand at Low Aggregation Levels—0
Improving Autoregressive NLP Tasks via Modular Linearized Attention—0
Comparative Study of MPPT and Parameter Estimation of PV cells—0
An Interpretable Approach to Load Profile Forecasting in Power Grids using Galerkin-Approximated Koopman PseudospectraCode0
FedBlockHealth: A Synergistic Approach to Privacy and Security in IoT-Enabled Healthcare through Federated Learning and Blockchain—0
Reconfigurable Intelligent Surface-Enabled Gridless DoA Estimation System for NLoS Scenarios—0
A Machine Learning-Enhanced Benders Decomposition Approach to Solve the Transmission Expansion Planning Problem under Uncertainty—0
Model Predictive Control with Self-supervised Representation LearningCode0
Dynamic Voxel Grid Optimization for High-Fidelity RGB-D Supervised Surface Reconstruction—0
Gradient-Free Textual Inversion—0
Scale-Space Hypernetworks for Efficient Biomedical Imaging—0
State estimation of a carbon capture process through POD model reduction and neural network approximation—0
Machine learning for structure-property relationships: Scalability and limitations—0
A Unified Framework for Exploratory Learning-Aided Community Detection Under Topological Uncertainty—0
One Transform To Compute Them All: Efficient Fusion-Based Full-Reference Video Quality Assessment—0
A Framework for Combustion Chemistry Acceleration with DeepONets—0
When approximate design for fast homomorphic computation provides differential privacy guarantees—0
Visualizing Skiers' Trajectories in Monocular Videos—0
Efficient CNNs via Passive Filter Pruning—0
A differentiable programming framework for spin modelsCode0
Tractable Identification of Electric Distribution Networks—0
On Degeneracy Issues in Multi-parametric Programming and Critical Region Exploration based Distributed Optimization in Smart Grid Operations—0
Propagating Parameter Uncertainty in Power System Nonlinear Dynamic Simulations Using a Koopman Operator-Based Surrogate Model—0
Polarity is all you need to learn and transfer fasterCode0
Efficient Alternating Minimization Solvers for Wyner Multi-View Unsupervised LearningCode0
GP-PCS: One-shot Feature-Preserving Point Cloud Simplification with Gaussian Processes on Riemannian ManifoldsCode0
On the Importance of Feature Separability in Predicting Out-Of-Distribution Error—0
NVAutoNet: Fast and Accurate 360^ 3D Visual Perception For Self Driving—0
Revisiting DeepFool: generalization and improvementCode0
Hardness of Independent Learning and Sparse Equilibrium Computation in Markov Games—0
A Novel and Optimal Spectral Method for Permutation Synchronization—0
Optimized preprocessing and Tiny ML for Attention State Classification—0
GNN-Assisted Phase Space Integration with Application to Atomistics—0
FD-Net: An Unsupervised Deep Forward-Distortion Model for Susceptibility Artifact Correction in EPICode0
A Spatio-temporal Decomposition Method for the Coordinated Economic Dispatch of Integrated Transmission and Distribution Grids—0
XVoxel-Based Parametric Design Optimization of Feature Models—0
HDformer: A Higher Dimensional Transformer for Diabetes Detection Utilizing Long Range Vascular Signals—0
All4One: Symbiotic Neighbour Contrastive Learning via Self-Attention and Redundancy ReductionCode0
Active Semi-Supervised Learning by Exploring Per-Sample Uncertainty and Consistency—0
Interpretable Ensembles of Hyper-Rectangles as Base ModelsCode0
Optimal Sampling Designs for Multi-dimensional Streaming Time Series with Application to Power Grid Sensor Data—0
NeurEPDiff: Neural Operators to Predict Geodesics in Deformation Spaces—0
Importance Filtering with Risk Models for Complex Driving Situations—0
Gradient-Descent Based Optimization of Constant Envelope OFDM Waveforms—0
BCSSN: Bi-direction Compact Spatial Separable Network for Collision Avoidance in Autonomous Driving—0
Gaussian Max-Value Entropy Search for Multi-Agent Bayesian OptimizationCode0
Scattering and Gathering for Spatially Varying Blurs—0
A pseudo-likelihood approach to community detection in weighted networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified