AI Agent - arXivDaily 专题

2112.01535 2021-12-20 eess.IV cs.AI cs.LG 62%

Robust End-to-End Focal Liver Lesion Detection using Unregistered Multiphase Computed Tomography Images

Sang-gil Lee, Eunji Kim, Jae Seok Bae, Jung Hoon Kim, Sungroh Yoon

专题命中工作流自动化：workflow(abstract)；分类 cs.AI、cs.LG

Comments IEEE TETCI. 14 pages, 8 figures, 5 tables

2112.08930 2021-12-17 cs.CV cs.AI cs.LG cs.MM stat.ML 62%

Intelli-Paint: Towards Developing Human-like Painting Agents

Jaskirat Singh, Cameron Smith, Jose Echevarria, Liang Zheng

专题命中工作流自动化：agent(abstract)；分类 cs.AI、cs.LG

2005.00840 2021-12-07 cs.LG cs.AI 62%

Decision Support for Intoxication Prediction Using Graph Convolutional Networks

Hendrik Burwinkel, Matthias Keicher, David Bani-Harouni, Tobias Zellner, Florian Eyer, Nassir Navab, Seyed-Ahmad Ahmadi

专题命中工作流自动化：workflow(abstract)；分类 cs.AI、cs.LG

Comments 10 pages, 3 figures

Journal ref Medical Image Computing and Computer Assisted Intervention (MICCAI 2020)

2111.02398 2021-11-05 eess.IV cs.AI cs.CV cs.LG 62%

Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods

Zohaib Salahuddin, Henry C Woodruff, Avishek Chatterjee, Philippe Lambin

专题命中工作流自动化：workflow(abstract)；分类 cs.AI、cs.LG

2110.10817 2021-10-22 stat.ML cs.CL cs.LG stat.AP 62%

The R package sentometrics to compute, aggregate and predict with textual sentiment

David Ardia, Keven Bluteau, Samuel Borms, Kris Boudt

专题命中工作流自动化：workflow(abstract)；分类 cs.CL、cs.LG

Journal ref Journal of Statistical Software, 2021, 99, 1-40

2110.10674 2021-10-22 cs.LG cs.AI 62%

SEA: Graph Shell Attention in Graph Neural Networks

Christian M. M. Frey, Yunpu Ma, Matthias Schubert

专题命中工作流自动化：workflow(abstract)；分类 cs.AI、cs.LG

2008.03229 2021-10-22 cs.AI cs.LG 62%

Towards Sample Efficient Agents through Algorithmic Alignment

Mingxuan Li, Michael L. Littman

专题命中工作流自动化：agent(abstract)；分类 cs.AI、cs.LG

2110.08253 2021-10-19 cs.LG cs.AI q-bio.GN 62%

A Field Guide to Scientific XAI: Transparent and Interpretable Deep Learning for Bioinformatics Research

Thomas P Quinn, Sunil Gupta, Svetha Venkatesh, Vuong Le

专题命中工作流自动化：workflow(abstract)；分类 cs.AI、cs.LG

2110.03097 2021-10-08 cs.LG cs.AI physics.app-ph stat.ME 62%

SWAT Watershed Model Calibration using Deep Learning

M. K. Mudunuru, K. Son, P. Jiang, X. Chen

专题命中工作流自动化：workflow(abstract)；分类 cs.AI、cs.LG

Comments 23

2110.01108 2021-10-05 cs.LG cs.AI cs.HC 62%

Human-Centered AI for Data Science: A Systematic Approach

Dakuo Wang, Xiaojuan Ma, April Yi Wang

专题命中工作流自动化：workflow(abstract)；分类 cs.AI、cs.LG

2108.02550 2021-10-05 cs.HC cs.AI cs.LG 62%

VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models

Furui Cheng, Dongyu Liu, Fan Du, Yanna Lin, Alexandra Zytek, Haomin Li, Huamin Qu, Kalyan Veeramachaneni

专题命中工作流自动化：workflow(abstract)；分类 cs.AI、cs.LG

Comments Accepted to IEEE VIS 2021, To Appeal in IEEE Transactions on Visualization and Computer Graphics

2110.00087 2021-10-04 cs.CV cs.AI cs.LG cs.RO 62%

Seeing Glass: Joint Point Cloud and Depth Completion for Transparent Objects

Haoping Xu, Yi Ru Wang, Sagi Eppel, Alàn Aspuru-Guzik, Florian Shkurti, Animesh Garg

专题命中工作流自动化：workflow(abstract)；分类 cs.AI、cs.LG

Comments Accepted for Oral at Conference on Robot Learning (CoRL) 2021; Haoping Xu and Yi Ru Wang contributed equally; 8 pages, 6 figures, 3 tables

2109.13388 2021-09-29 cs.LG cs.AI cs.HC 62%

Go-Blend behavior and affect

Matthew Barthet, Antonios Liapis, Georgios N. Yannakakis

专题命中工作流自动化：agent(abstract)；分类 cs.AI、cs.LG

Comments 8 pages

2011.12956 2021-09-21 cs.LG cs.AI cs.RO cs.SY eess.SY 62%

Reinforcement Learning for Robust Missile Autopilot Design

Bernardo Cortez

专题命中工作流自动化：agent(abstract)；分类 cs.AI、cs.LG

Comments ICRLCT 2021 conference paper

2007.01544 2021-09-21 cs.AI cs.LG cs.MA 62%

A Conceptual Framework for Externally-influenced Agents: An Assisted Reinforcement Learning Review

Adam Bignold, Francisco Cruz, Matthew E. Taylor, Tim Brys, Richard Dazeley, Peter Vamplew, Cameron Foale

专题命中工作流自动化：agent(abstract)；分类 cs.AI、cs.LG

Comments 33 pages, 9 figures

2109.05866 2021-09-14 cs.LG cs.AI 62%

On Solving a Stochastic Shortest-Path Markov Decision Process as Probabilistic Inference

Mohamed Baioumy, Bruno Lacerda, Paul Duckworth, Nick Hawes

专题命中工作流自动化：planning(abstract)；分类 cs.AI、cs.LG

Comments Presented at the second International Workshop on Active Inference (IWAI 2021); 11 pages, 2 figures

2103.01834 2021-09-03 cs.CL cs.AI 62%

A Data-Centric Framework for Composable NLP Workflows

Zhengzhong Liu, Guanxiong Ding, Avinash Bukkittu, Mansi Gupta, Pengzhi Gao, Atif Ahmed, Shikun Zhang, Xin Gao, Swapnil Singhavi, Linwei Li, Wei Wei, Zecong Hu, Haoran Shi, Haoying Zhang, Xiaodan Liang, Teruko Mitamura, Eric P. Xing, Zhiting Hu

专题命中工作流自动化：workflow(abstract)；分类 cs.AI、cs.CL

Comments 8 pages, 4 figures, EMNLP 2020

2002.05259 2021-08-11 cs.AI cs.LG 62%

Learning to Generate Levels From Nothing

Philip Bontrager, Julian Togelius

专题命中工作流自动化：agent(abstract)；分类 cs.AI、cs.LG

Comments 8 pages, 8 figures. Accepted to the 3rd IEEE Conference On Games (COG 2021)

2108.00887 2021-08-10 cs.LG cs.AI 62%

A Machine learning approach for rapid disaster response based on multi-modal data. The case of housing & shelter needs

Karla Saldana Ochoa, Tina Comes

专题命中工作流自动化：workflow(abstract)；分类 cs.AI、cs.LG

2108.02662 2021-08-06 cs.LG cs.AI cs.CY 62%

Reducing Unintended Bias of ML Models on Tabular and Textual Data

Guilherme Alves, Maxime Amblard, Fabien Bernier, Miguel Couceiro, Amedeo Napoli

专题命中工作流自动化：workflow(abstract)；分类 cs.AI、cs.LG

Comments 10 pages, 2 figures, 11 tables, to be published in DSAA 2021

2107.14037 2021-07-30 cs.LG cs.AI 62%

Machine Learning and Deep Learning Methods for Building Intelligent Systems in Medicine and Drug Discovery: A Comprehensive Survey

G Jignesh Chowdary, Suganya G, Premalatha M, Asnath Victy Phamila Y, Karunamurthy K

专题命中工作流自动化：workflow(abstract)；分类 cs.AI、cs.LG

2107.13944 2021-07-30 cs.LG cs.AI stat.ML 62%

Lyapunov-based uncertainty-aware safe reinforcement learning

Ashkan B. Jeddi, Nariman L. Dehghani, Abdollah Shafieezadeh

专题命中工作流自动化：agent(abstract)；分类 cs.AI、cs.LG

Comments Submitted to IEEE Transactions on Neural Networks and Learning Systems

2107.12533 2021-07-28 cs.LG cs.AI 62%

Toward Co-creative Dungeon Generation via Transfer Learning

Zisen Zhou, Matthew Guzdial

专题命中工作流自动化：agent(abstract)；分类 cs.AI、cs.LG

Comments 7 pages, 6 figures, Workshop on Procedural Content Generation

Journal ref Proceedings of the Twelfth Workshop on Procedural Content Generation 2021

2107.08815 2021-07-20 cs.LG cs.AI 62%

Boosting the Convergence of Reinforcement Learning-based Auto-pruning Using Historical Data

Jiandong Mu, Mengdi Wang, Feiwen Zhu, Jun Yang, Wei Lin, Wei Zhang

专题命中工作流自动化：agent(abstract)；分类 cs.AI、cs.LG

2107.08194 2021-07-20 cs.NI cs.AI cs.LG 62%

Towards autonomic orchestration of machine learning pipelines in future networks

Abhishek Dandekar

专题命中工作流自动化：planning(abstract)；分类 cs.AI、cs.LG

2107.06639 2021-07-15 cs.PL cs.AI cs.LG 62%

You Only Write Thrice: Creating Documents, Computational Notebooks and Presentations From a Single Source

Kacper Sokol, Peter Flach

专题命中工作流自动化：workflow(abstract)；分类 cs.AI、cs.LG

Comments Published at Rethinking ML Papers -- ICLR 2021 Workshop. OpenReview: https://openreview.net/forum?id=i4zpuNRiU4G Exhibit: https://so-cool.github.io/you-only-write-thrice/

1812.02632 2021-07-09 cs.LG cs.AI stat.ML 62%

Active Deep Q-learning with Demonstration

Si-An Chen, Voot Tangkaratt, Hsuan-Tien Lin, Masashi Sugiyama

专题命中工作流自动化：agent(abstract)；分类 cs.AI、cs.LG

Journal ref Mach Learn 109, 1699-1725 (2020)

2009.10513 2021-06-11 cs.LG cs.AI stat.ML 62%

Local Post-Hoc Explanations for Predictive Process Monitoring in Manufacturing

Nijat Mehdiyev, Peter Fettke

专题命中工作流自动化：planning(abstract)；分类 cs.AI、cs.LG

Comments Accepted for publication in ECIS-2021 Proceedings (initial submission November 18, 2020). This version is an extension of the previous arXiv version

Journal ref ECIS 2021 Research Papers. 35 (2021) https://aisel.aisnet.org/ecis2021_rp/35

2105.03844 2021-05-11 cs.LG cs.AI q-fin.TR 62%

Reinforcement Learning with Expert Trajectory For Quantitative Trading

Sihang Chen, Weiqi Luo, Chao Yu

专题命中工作流自动化：agent(abstract)；分类 cs.AI、cs.LG

2104.14644 2021-05-03 cs.LG cs.AI 62%

What is Going on Inside Recurrent Meta Reinforcement Learning Agents?

Safa Alver, Doina Precup

专题命中工作流自动化：agent(abstract)；分类 cs.AI、cs.LG

Comments Accepted to the Never-Ending Reinforcement Learning Workshop at ICLR 2021

1. 工作流自动化 10492 篇

Robust End-to-End Focal Liver Lesion Detection using Unregistered Multiphase Computed Tomography Images

Intelli-Paint: Towards Developing Human-like Painting Agents

Decision Support for Intoxication Prediction Using Graph Convolutional Networks

Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods

The R package sentometrics to compute, aggregate and predict with textual sentiment

SEA: Graph Shell Attention in Graph Neural Networks

Towards Sample Efficient Agents through Algorithmic Alignment

A Field Guide to Scientific XAI: Transparent and Interpretable Deep Learning for Bioinformatics Research

SWAT Watershed Model Calibration using Deep Learning

Human-Centered AI for Data Science: A Systematic Approach

VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models

Seeing Glass: Joint Point Cloud and Depth Completion for Transparent Objects

Go-Blend behavior and affect

Reinforcement Learning for Robust Missile Autopilot Design

A Conceptual Framework for Externally-influenced Agents: An Assisted Reinforcement Learning Review

On Solving a Stochastic Shortest-Path Markov Decision Process as Probabilistic Inference

A Data-Centric Framework for Composable NLP Workflows

Learning to Generate Levels From Nothing

A Machine learning approach for rapid disaster response based on multi-modal data. The case of housing & shelter needs

Reducing Unintended Bias of ML Models on Tabular and Textual Data

Machine Learning and Deep Learning Methods for Building Intelligent Systems in Medicine and Drug Discovery: A Comprehensive Survey

Lyapunov-based uncertainty-aware safe reinforcement learning

Toward Co-creative Dungeon Generation via Transfer Learning

Boosting the Convergence of Reinforcement Learning-based Auto-pruning Using Historical Data

Towards autonomic orchestration of machine learning pipelines in future networks

You Only Write Thrice: Creating Documents, Computational Notebooks and Presentations From a Single Source

Active Deep Q-learning with Demonstration

Local Post-Hoc Explanations for Predictive Process Monitoring in Manufacturing

Reinforcement Learning with Expert Trajectory For Quantitative Trading

What is Going on Inside Recurrent Meta Reinforcement Learning Agents?