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 2301–2325 of 4891 papers

TitleStatusHype
High Order Collaboration-Oriented Federated Graph Neural Network for Accurate QoS Prediction—0
HSfM: Hybrid Structure-from-Motion—0
HSIDMamba: Exploring Bidirectional State-Space Models for Hyperspectral Denoising—0
HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks—0
HTMD-Net: A Hybrid Masking-Denoising Approach to Time-Domain Monaural Singing Voice Separation—0
Deep Adaptive Interest Network: Personalized Recommendation with Context-Aware Learning—0
Human Activity Recognition Using Cascaded Dual Attention CNN and Bi-Directional GRU Framework—0
Effective Probabilistic Time Series Forecasting with Fourier Adaptive Noise-Separated Diffusion—0
High Fidelity Text-to-Speech Via Discrete Tokens Using Token Transducer and Group Masked Language Model—0
Hybrid Adaptive Modeling using Neural Networks Trained with Nonlinear Dynamics Based Features—0
Hybrid Algorithm Selection and Hyperparameter Tuning on Distributed Machine Learning Resources: A Hierarchical Agent-based Approach—0
A Survey on Computationally Efficient Neural Architecture Search—0
Hybrid Deep Learning for Legal Text Analysis: Predicting Punishment Durations in Indonesian Court Rulings—0
Hybrid Firefly-Genetic Algorithm for Single and Multi-dimensional 0-1 Knapsack Problems—0
A Survey on the Integration of Machine Learning with Sampling-based Motion Planning—0
Integrating Agent-Based and Compartmental Models for Infectious Disease Modeling: A Novel Hybrid Approach—0
NeuralFactors: A Novel Factor Learning Approach to Generative Modeling of Equities—0
Hybrid machine learning based scale bridging framework for permeability prediction of fibrous structures—0
DCT-SNN: Using DCT To Distribute Spatial Information Over Time for Low-Latency Spiking Neural Networks—0
High-fidelity Multiphysics Modelling for Rapid Predictions Using Physics-informed Parallel Neural Operator—0
Hybrid Real- and Complex-valued Neural Network Architecture—0
Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Vision—0
Hybrid Supervised and Reinforcement Learning for the Design and Optimization of Nanophotonic Structures—0
Hybrid Temporal Differential Consistency Autoencoder for Efficient and Sustainable Anomaly Detection in Cyber-Physical Systems—0
Higher Order Transformers: Efficient Attention Mechanism for Tensor Structured Data—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified