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Computational Efficiency

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보존된 평가 기록: 1

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.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/qslim/pdf

공식 코드

Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering

https://github.com/r-j96/stainfuser

공식 코드

StainFuser: Controlling Diffusion for Faster Neural Style Transfer in Multi-Gigapixel Histology Images

https://github.com/rachtibat/lrp-explains-transformers

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AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers

https://github.com/rachtibat/lrp-for-transformers

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AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers

https://github.com/radarFudan/mamba

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Mamba: Linear-Time Sequence Modeling with Selective State Spaces

https://github.com/raffoliveira/ts2vvg

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Leveraging Visibility Graphs for Enhanced Arrhythmia Classification with Graph Convolutional Networks

https://github.com/raffoliveira/vg_for_arrhythmia_classification_with_gcn

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Leveraging Visibility Graphs for Enhanced Arrhythmia Classification with Graph Convolutional Networks

https://github.com/rafusan/dl-alzheimer

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Deep Learning for Early Alzheimer Disease Detection with MRI Scans

https://github.com/rahul-gs-16/sdlformer

공식 코드

SDLFormer: A Sparse and Dense Locality-enhanced Transformer for Accelerated MR Image Reconstruction

https://github.com/raminzandvakili/l0-qsvm

공식 코드

Sparse L0-norm based Kernel-free Quadratic Surface Support Vector Machines

https://github.com/raoofnaushad/eurosat_lulc

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Deep Transfer Learning for Land Use and Land Cover Classification: A Comparative Study

https://github.com/rasoulnajafi/microstructure-embedded-autoencoder-mea-

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Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric space

https://github.com/ravi-chepuri/hybrid_rc_ngrc

공식 코드

Hybridizing Traditional and Next-Generation Reservoir Computing to Accurately and Efficiently Forecast Dynamical Systems

https://github.com/rayleizhu/biformer

공식 코드

BiFormer: Vision Transformer with Bi-Level Routing Attention

https://github.com/raynbowy23/fedmeta-geolane

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Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection

https://github.com/razaimam45/fine-tune-distillation

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Domain Adaptable Fine-Tune Distillation Framework For Advancing Farm Surveillance

https://github.com/razaimam45/seda

공식 코드

SEDA: Self-Ensembling ViT with Defensive Distillation and Adversarial Training for robust Chest X-rays Classification

https://github.com/remigenet/TLN

공식 코드

A Temporal Linear Network for Time Series Forecasting

https://github.com/remigenet/deepdynamicvwap

공식 코드

Recurrent Neural Networks for Dynamic VWAP Execution: Adaptive Trading Strategies with Temporal Kolmogorov-Arnold Networks

https://github.com/remosasso/psdrl

공식 코드

Posterior Sampling for Deep Reinforcement Learning

https://github.com/renchunzi-xie/mano

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MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts

https://github.com/rhshi/sparse-rf

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SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning

https://github.com/richardobi/frd-score

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Fréchet Radiomic Distance (FRD): A Versatile Metric for Comparing Medical Imaging Datasets

https://github.com/riktor/safer2-recommender

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Safe Collaborative Filtering

https://github.com/ringbdstack/drl-dbscan

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Automating DBSCAN via Deep Reinforcement Learning

https://github.com/rmclarke/adamthroughasecondorderlens

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Studying K-FAC Heuristics by Viewing Adam through a Second-Order Lens

https://github.com/rmphys/tnrc_paper

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A tensor network approach for chaotic time series prediction

https://github.com/rmusab/hpclust

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High-Performance Hybrid Algorithm for Minimum Sum-of-Squares Clustering of Infinitely Tall Data

https://github.com/roatienza/deep-text-recognition-benchmark

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Vision Transformer for Fast and Efficient Scene Text Recognition

https://github.com/robertleppich/rep-net

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Decomposing the Time Series Forecasting Pipeline: A Modular Approach for Time Series Representation, Information Extraction, and Projection

https://github.com/rohdelab/rcdt_ns_classifier

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Radon cumulative distribution transform subspace modeling for image classification

https://github.com/ronigold/TokenSHAP

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TokenSHAP: Interpreting Large Language Models with Monte Carlo Shapley Value Estimation

https://github.com/rooshenas/ebr_mt

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Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models

https://github.com/rose-stl-lab/dyffusion

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DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

https://github.com/rottenivy/mv_pts_correlatederr

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Multivariate Probabilistic Time Series Forecasting with Correlated Errors

https://github.com/rsai-lab/hdmba

공식 코드

HDMba: Hyperspectral Remote Sensing Imagery Dehazing with State Space Model

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