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 471–480 of 4891 papers

TitleStatusHype
Does Vector Quantization Fail in Spatio-Temporal Forecasting? Exploring a Differentiable Sparse Soft-Vector Quantization ApproachCode1
Spatially Covariant Image Registration with Text PromptsCode1
Automated Lane Merging via Game Theory and Branch Model Predictive ControlCode1
Latent Diffusion Prior Enhanced Deep Unfolding for Snapshot Spectral Compressive ImagingCode1
Toward Efficient and Incremental Spectral Clustering via Parametric Spectral ClusteringCode1
Real-Time Machine-Learning-Based Optimization Using Input Convex Long Short-Term Memory NetworkCode1
Quantized Distillation: Optimizing Driver Activity Recognition Models for Resource-Constrained EnvironmentsCode1
Improving Computational Efficiency for Powered Descent Guidance via Transformer-based Tight Constraint PredictionCode1
Solving High Frequency and Multi-Scale PDEs with Gaussian ProcessesCode1
Mixed Models with Multiple Instance LearningCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified