Computational Efficiency
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Benchmarks
Plant village
Most implemented
Rethinking the Inception Architecture for Computer Vision
Attention U-Net: Learning Where to Look for the Pancreas
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies
Simple random search provides a competitive approach to reinforcement learning
Papers
TACO: Ternary Absolute-max Column-wise One-sparse Optimizer for LLM Fine-Tuning
Full-parameter fine-tuning of large language models (LLMs) incurs substantial optimizer state memory overhead, limiting the model sizes that fit on modern GPUs. Existing approaches either compress optimizer state, abando…
Computational EfficiencyHunyuan-A13B Technical Report
We present Hunyuan-A13B, an open-source large language model based on a Mixture-of-Experts architecture. It contains 80 billion total parameters but activates only 13 billion during inference, balancing model capability,…
Computational EfficiencyReinforcement LearningA unified framework for global and local interpretability using adaptive derivative-ordered random explanation
The interpretability of complex machine learning models is of paramount importance, especially in real-world high-stakes domains such as healthcare and finance. However, existing post-hoc interpretability methods suffer …
Computational EfficiencyFeature ImportanceHigh-Fidelity Digital Twin Data Models by Randomized Dynamic Mode Decomposition and Deep Learning with Applications in Fluid Dynamics
The purpose of this paper is the identification of high-fidelity digital twin data models from numerical code outputs by non-intrusive techniques (i.e., not requiring Galerkin projection of the governing equations onto t…
Computational EfficiencyEfficient 3D Whole-Body PET Image Denoising via Conditional Rectified Flow With Optimized Sampling Strategy
Reducing radiation exposure in Positron Emission Tomography (PET) is important for patient safety; however, ultra-low-dose imaging suffers from severe noise, which may affect diagnostic interpretation without appropriate…
Computational EfficiencyImage EnhancementImage DenoisingA Bio-Plausible Visual Neural Network for Locust-Inspired Collision Perception
Locust visual systems have long served as an important biological paradigm for studying looming perception and collision avoidance. Numerous computational models have successfully reproduced the selective responses of Lo…
Computational EfficiencyCollision Avoidance