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 2951–2975 of 4891 papers

TitleStatusHype
RRWKV: Capturing Long-range Dependencies in RWKV—0
Sequence-to-Sequence Model with Transformer-based Attention Mechanism and Temporal Pooling for Non-Intrusive Load Monitoring—0
An adaptive augmented Lagrangian method for training physics and equality constrained artificial neural networksCode1
Estimating Koopman operators with sketching to provably learn large scale dynamical systemsCode1
Stochastic Natural Thresholding Algorithms—0
Robust-DefReg: A Robust Deformable Point Cloud Registration Method based on Graph Convolutional Neural Networks—0
FAMO: Fast Adaptive Multitask OptimizationCode1
Proximal Symmetric Non-negative Latent Factor Analysis: A Novel Approach to Highly-Accurate Representation of Undirected Weighted Networks—0
Exploring the effects of robotic design on learning and neural controlCode0
The Power Of Simplicity: Why Simple Linear Models Outperform Complex Machine Learning Techniques -- Case Of Breast Cancer Diagnosis—0
DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal ForecastingCode2
Content-aware Token Sharing for Efficient Semantic Segmentation with Vision TransformersCode1
Overcoming the Stability Gap in Continual Learning—0
Do we become wiser with time? On causal equivalence with tiered background knowledge—0
Interaction Measures, Partition Lattices and Kernel Tests for High-Order InteractionsCode0
TorchRL: A data-driven decision-making library for PyTorchCode4
Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesisCode4
Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary DomainsCode1
ELSA: Efficient Label Shift Adaptation through the Lens of Semiparametric Models—0
Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria RecommendationCode0
Identification of stormwater control strategies and their associated uncertainties using Bayesian OptimizationCode0
Caterpillar: A Pure-MLP Architecture with Shifted-Pillars-ConcatenationCode0
Fourier-DeepONet: Fourier-enhanced deep operator networks for full waveform inversion with improved accuracy, generalizability, and robustness—0
Bi-fidelity Variational Auto-encoder for Uncertainty QuantificationCode0
Neural incomplete factorization: learning preconditioners for the conjugate gradient methodCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified