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 1501–1525 of 4891 papers

TitleStatusHype
A Walsh Hadamard Derived Linear Vector Symbolic ArchitectureCode1
Self-Driving Car Racing: Application of Deep Reinforcement Learning—0
SkipSNN: Efficiently Classifying Spike Trains with Event-attentionCode0
Bayesian Quantum Neural Network for Renewable-Rich Power Flow with Training Efficiency and Generalization Capability Improvements—0
Denoising Diffusion Probabilistic Models for Magnetic Resonance Fingerprinting—0
AI-assisted Agile Propagation Modeling for Real-time Digital Twin Wireless Networks—0
Breast Cancer Histopathology Classification using CBAM-EfficientNetV2 with Transfer Learning—0
Bayesian Optimization for Hyperparameters Tuning in Neural Networks—0
Dual Conditional Diffusion Models for Sequential Recommendation—0
Gnothi Seauton: Empowering Faithful Self-Interpretability in Black-Box Transformers—0
Carbon-Aware Computing for Data Centers with Probabilistic Performance Guarantees—0
Quantum Reinforcement Learning-Based Two-Stage Unit Commitment Framework for Enhanced Power Systems Robustness—0
ATLAS: Adapting Trajectory Lengths and Step-Size for Hamiltonian Monte CarloCode0
A Temporal Linear Network for Time Series ForecastingCode0
Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent CodingCode1
Long Sequence Modeling with Attention Tensorization: From Sequence to Tensor Learning—0
Neural Hamilton: Can A.I. Understand Hamiltonian Mechanics?Code1
Efficient Bilinear Attention-based Fusion for Medical Visual Question Answering—0
Fast Calibrated Explanations: Efficient and Uncertainty-Aware Explanations for Machine Learning ModelsCode2
Optimal Hardening Strategy for Electricity-Hydrogen Networks with Hydrogen Leakage Risk Control against Extreme Weather—0
Lodge++: High-quality and Long Dance Generation with Vivid Choreography Patterns—0
Accelerating Direct Preference Optimization with Prefix SharingCode2
Enhancing CNN Classification with Lamarckian Memetic Algorithms and Local Search—0
CGKN: A Deep Learning Framework for Modeling Complex Dynamical Systems and Efficient Data AssimilationCode0
Prompt Diffusion Robustifies Any-Modality Prompt Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified