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 1051–1060 of 4891 papers

TitleStatusHype
GraphGAN: Graph Representation Learning with Generative Adversarial NetsCode0
Graph Neural Networks for modelling breast biomechanical compressionCode0
Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical ModelsCode0
Grafting for Combinatorial Boolean Model using Frequent Itemset MiningCode0
Bisimulation metric for Model Predictive ControlCode0
Language Models with TransformersCode0
Granular Ball Twin Support Vector MachineCode0
Hard constraint learning approaches with trainable influence functions for evolutionary equationsCode0
Image Classification with CondenseNeXt for ARM-Based Computing PlatformsCode0
BIP: Boost Invariant Polynomials for Efficient Jet TaggingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified