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 3101–3125 of 4891 papers

TitleStatusHype
An Autonomous Vision-Based Algorithm for Interplanetary Navigation—0
Asynchronous Perception-Action-Communication with Graph Neural Networks—0
Decoder-only Architecture for Speech Recognition with CTC Prompts and Text Data Augmentation—0
FrameRS: A Video Frame Compression Model Composed by Self supervised Video Frame Reconstructor and Key Frame SelectorCode0
Astrocyte-Integrated Dynamic Function Exchange in Spiking Neural Networks—0
Efficient Polyp Segmentation Via Integrity Learning—0
Scaling Laws for Sparsely-Connected Foundation Models—0
Optimizing Deep Decarbonization Pathways in California with Power System Planning Using Surrogate Level-based Lagrangian Relaxation—0
Native Language Identification with Big Bird EmbeddingsCode0
Geometry Enhanced Optimal Control Technique for Acrobatic Flip Motion of Quadcopter—0
Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion ModelsCode0
Hybrid Algorithm Selection and Hyperparameter Tuning on Distributed Machine Learning Resources: A Hierarchical Agent-based Approach—0
Computation of safe disturbance sets using implicit RPI sets—0
LMBiS-Net: A Lightweight Multipath Bidirectional Skip Connection based CNN for Retinal Blood Vessel SegmentationCode0
Effective Real Image Editing with Accelerated Iterative Diffusion Inversion—0
HAct: Out-of-Distribution Detection with Neural Net Activation Histograms—0
Short-Term Load Forecasting Using A Particle-Swarm Optimized Multi-Head Attention-Augmented CNN-LSTM Network—0
CLEANing Cygnus A deep and fast with R2D2—0
Priority Queue Formulation of Agent-Based Bathtub Model for Network Trip Flows in the Relative Space—0
ADC/DAC-Free Analog Acceleration of Deep Neural Networks with Frequency Transformation—0
Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits—0
Structured Radial Basis Function Network: Modelling Diversity for Multiple Hypotheses Prediction—0
Multi-stage Deep Learning Artifact Reduction for Pallel-beam Computed Tomography—0
Artificial to Spiking Neural Networks Conversion for Scientific Machine Learning—0
Communication-Efficient Decentralized Federated Learning via One-Bit Compressive Sensing—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified