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 2276–2300 of 4891 papers

TitleStatusHype
Learning-based model augmentation with LFRsCode0
Tensorized NeuroEvolution of Augmenting Topologies for GPU AccelerationCode3
Complex Neural Network based Joint AoA and AoD Estimation for Bistatic ISACCode1
MugenNet: A Novel Combined Convolution Neural Network and Transformer Network with its Application for Colonic Polyp Image Segmentation—0
A Novel Feature Map Enhancement Technique Integrating Residual CNN and Transformer for Alzheimer Diseases Diagnosis—0
Computation and Communication Efficient Lightweighting Vertical Federated Learning for Smart Building IoT—0
SelfReplay: Adapting Self-Supervised Sensory Models via Adaptive Meta-Task Replay—0
P-Hologen: An End-to-End Generative Framework for Phase-Only HologramsCode0
Learning Enriched Features via Selective State Spaces Model for Efficient Image DeblurringCode1
Reachability Analysis Using Constrained Polynomial Logical ZonotopesCode0
Multi-scale Unified Network for Image Classification—0
Transformers-based architectures for stroke segmentation: A review—0
Retentive Decision Transformer with Adaptive Masking for Reinforcement Learning based Recommendation Systems—0
Tiny Models are the Computational Saver for Large ModelsCode0
CCDSReFormer: Traffic Flow Prediction with a Criss-Crossed Dual-Stream Enhanced Rectified Transformer Model—0
Hawk: Accurate and Fast Privacy-Preserving Machine Learning Using Secure Lookup Table Computation—0
Grappa -- A Machine Learned Molecular Mechanics Force FieldCode2
Benchmarking Video Frame Interpolation—0
ModeTv2: GPU-accelerated Motion Decomposition Transformer for Pairwise Optimization in Medical Image RegistrationCode1
Understanding the Functional Roles of Modelling Components in Spiking Neural Networks—0
Stochastic parameter reduced-order model based on hybrid machine learning approaches—0
Crypto Inverse-Power Options and Fractional Stochastic Volatility—0
Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering RefinementCode3
A Unified Module for Accelerating STABLE-DIFFUSION: LCM-LORA—0
Fast and Unified Path Gradient Estimators for Normalizing Flows—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified