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 1476–1500 of 4891 papers

TitleStatusHype
Deep operator neural network applied to efficient computation of asteroid surface temperature and the Yarkovsky effect—0
How Analysis Can Teach Us the Optimal Way to Design Neural Operators—0
Real-Time Polygonal Semantic Mapping for Humanoid Robot Stair ClimbingCode2
An algorithm for two-player repeated games with imperfect public monitoringCode0
Flexible Coded Distributed Convolution Computing for Enhanced Fault Tolerance and Numerical Stability in Distributed CNNs—0
Quantum Rationale-Aware Graph Contrastive Learning for Jet Discrimination—0
HC^3L-Diff: Hybrid conditional latent diffusion with high frequency enhancement for CBCT-to-CT synthesis—0
Federated Learning with Relative Fairness—0
Cross-D Conv: Cross-Dimensional Transferable Knowledge Base via Fourier Shifting OperationCode0
WaKA: Data Attribution using K-Nearest Neighbors and Membership Privacy Principles—0
An Efficient Hierarchical Preconditioner-Learner Architecture for Reconstructing Multi-scale Basis Functions of High-dimensional Subsurface Fluid Flow—0
Modern, Efficient, and Differentiable Transport Equation Models using JAX: Applications to Population Balance Equations—0
SANN-PSZ: Spatially Adaptive Neural Network for Head-Tracked Personal Sound Zones—0
Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-OptimizationCode2
3D Equivariant Pose Regression via Direct Wigner-D Harmonics Prediction—0
Birdie: Advancing State Space Models with Reward-Driven Objectives and CurriculaCode1
Meta-Sealing: A Revolutionizing Integrity Assurance Protocol for Transparent, Tamper-Proof, and Trustworthy AI System—0
Evaluating the Evolution of YOLO (You Only Look Once) Models: A Comprehensive Benchmark Study of YOLO11 and Its Predecessors—0
An Empirical Analysis of Speech Self-Supervised Learning at Multiple Resolutions—0
ψDAG: Projected Stochastic Approximation Iteration for DAG Structure LearningCode0
Leveraging Large Language Models for Medical Information Extraction and Query Generation—0
Constrained Trajectory Optimization for Hybrid Dynamical Systems—0
Comparative Analysis of Demonstration Selection Algorithms for LLM In-Context LearningCode1
BUZZ: Beehive-structured Sparse KV Cache with Segmented Heavy Hitters for Efficient LLM InferenceCode0
Self-Driving Car Racing: Application of Deep Reinforcement Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified