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Computational Efficiency

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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/maxramgraber/ensemble-transport-smoothing-part-i

공식 코드

Ensemble transport smoothing. Part I: Unified framework

https://github.com/maxwelljones14/efficient-ssl

공식 코드

Efficiently Learning the Graph for Semi-supervised Learning

https://github.com/maxxxzdn/erwin

공식 코드

Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems

https://github.com/maxzanella/mta

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On the test-time zero-shot generalization of vision-language models: Do we really need prompt learning?

https://github.com/mazhengcn/deeprte

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DeepRTE: Pre-trained Attention-based Neural Network for Radiative Tranfer

https://github.com/mazurowski-lab/RaD

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

https://github.com/mazurowski-lab/medical-image-similarity-metrics

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

https://github.com/mbilos/neural-flows-experiments

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Neural Flows: Efficient Alternative to Neural ODEs

https://github.com/mc-e/transcl

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TransCL: Transformer Makes Strong and Flexible Compressive Learning

https://github.com/mc4117/ResNet_Weather

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Combining distribution-based neural networks to predict weather forecast probabilities

https://github.com/mcgrche/LetsPi--Planning-Safety-Trajectories-with-Dual-Phase-Physics-Informed-LLM

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Planning Safety Trajectories with Dual-Phase, Physics-Informed, and Transportation Knowledge-Driven Large Language Models

https://github.com/mdaamirQ/2-QNSCD

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Quantum Natural Stochastic Pairwise Coordinate Descent

https://github.com/mdi-tokyotech/efficient_and_accurate_full-waveform_inversion_with_total_variation_constraint

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Efficient and Accurate Full-Waveform Inversion with Total Variation Constraint

https://github.com/mdk31/causalbootstrap

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A Fast Bootstrap Algorithm for Causal Inference with Large Data

https://github.com/med-air/interactive-registration

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Toward Reliable AR-Guided Surgical Navigation: Interactive Deformation Modeling with Data-Driven Biomechanics and Prompts

https://github.com/medicl-vu/oct-mosaicking

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Novel OCT mosaicking pipeline with Feature- and Pixel-based registration

https://github.com/medvic-lab/efficient_morph_registration

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EfficientMorph: Parameter-Efficient Transformer-Based Architecture for 3D Image Registration

https://github.com/menelau/mlrs-pds

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MLRS-PDS: A Meta-learning recommendation of dynamic ensemble selection pipelines

https://github.com/meowoodie/Spatio-Temporal-Point-Process-with-Gaussian-Mixture-Diffusion-Kernel

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Imitation Learning of Neural Spatio-Temporal Point Processes

https://github.com/metaevo/awesome-metabbo

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Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-Optimization

https://github.com/meteahishali/osen

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Operational Support Estimator Networks

https://github.com/metnetcomp/dbgdel

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DBgDel: Database-Enhanced Gene Deletion Framework for Growth-Coupled Production in Genome-Scale Metabolic Models

https://github.com/mever-team/distill-and-select

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DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval

https://github.com/mfigurnov/sact

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Spatially Adaptive Computation Time for Residual Networks

https://github.com/mgb45/mkfbodytracker_pdaf

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Single camera pose estimation using Bayesian filtering and Kinect motion priors

https://github.com/mhassann22/GCSAM

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GCSAM: Gradient Centralized Sharpness Aware Minimization

https://github.com/miannaeem-lab/lemore

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LeMoRe: Learn More Details for Lightweight Semantic Segmentation

https://github.com/miaoqiaowei/awesome-4d

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Advances in 4D Generation: A Survey

https://github.com/mic-dkfz/foreground-and-anonymization-area-segmentation

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A Unified Framework for Foreground and Anonymization Area Segmentation in CT and MRI Data

https://github.com/microsoft/DeepSpeed

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ZeRO-Offload: Democratizing Billion-Scale Model Training

https://github.com/microsoft/SGN

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Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition

https://github.com/microsoft/StyleSwin

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StyleSwin: Transformer-based GAN for High-resolution Image Generation

https://github.com/microsoft/efficientlongsequencemodeling

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Efficient Long Sequence Modeling via State Space Augmented Transformer

https://github.com/microsoft/encoder-decoder-slm

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Return of the Encoder: Maximizing Parameter Efficiency for SLMs

https://github.com/microsoft/healthcareai-examples

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Multi-Modal Mamba Modeling for Survival Prediction (M4Survive): Adapting Joint Foundation Model Representations

https://github.com/microsoft/robustlearn

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SpecFormer: Guarding Vision Transformer Robustness via Maximum Singular Value Penalization

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.