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

Showing 37513775 of 4891 papers

TitleStatusHype
NeurAll: Towards a Unified Visual Perception Model for Automated Driving0
Neural network based control of unknown nonlinear systems via contraction analysis0
Neural Network-based Information-Theoretic Transceivers for High-Order Modulation Schemes0
Neural network-enhanced integrators for simulating ordinary differential equations0
Neural Open Information Extraction0
Neural Parameter Regression for Explicit Representations of PDE Solution Operators0
Neural Theorem Provers Delineating Search Area Using RNN0
NeurEPDiff: Neural Operators to Predict Geodesics in Deformation Spaces0
NeurIPS 2024 ML4CFD Competition: Harnessing Machine Learning for Computational Fluid Dynamics in Airfoil Design0
NeurIPS 2024 ML4CFD Competition: Results and Retrospective Analysis0
NeurLZ: An Online Neural Learning-Based Method to Enhance Scientific Lossy Compression0
Neuromorphic Digital-Twin-based Controller for Indoor Multi-UAV Systems Deployment0
Neuromorphic Electronic Systems for Reservoir Computing0
Neuromorphic Optical Tracking and Imaging of Randomly Moving Targets through Strongly Scattering Media0
Neuromorphic Robust Estimation of Nonlinear Dynamical Systems Applied to Satellite Rendezvous0
Neuromorphic Spintronics0
NeuroPAL: Punctuated Anytime Learning with Neuroevolution for Macromanagement in Starcraft: Brood War0
NeuroSleepNet: A Multi-Head Self-Attention Based Automatic Sleep Scoring Scheme with Spatial and Multi-Scale Temporal Representation Learning0
New keypoint-based approach for recognising British Sign Language (BSL) from sequences0
New Routes to Phylogeography0
Next-Best-Trajectory Planning of Robot Manipulators for Effective Observation and Exploration0
NGPU-LM: GPU-Accelerated N-Gram Language Model for Context-Biasing in Greedy ASR Decoding0
NIDA-CLIFGAN: Natural Infrastructure Damage Assessment through Efficient Classification Combining Contrastive Learning, Information Fusion and Generative Adversarial Networks0
Centrality-Based Node Feature Augmentation for Robust Network Alignment0
Node Similarities under Random Projections: Limits and Pathological Cases0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified