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Author search results
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- Matthew Taylor — disambiguation page
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- Matthew E. Taylor
aka: Matthew Edmund Taylor - Matthew Rutledge-Taylor
- Matthew P. Taylor
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Publication search results
found 591 matches
- 2024
- Carl Orge Retzlaff, Srijita Das, Christabel Wayllace, Payam Mousavi, Mohammad Afshari, Tianpei Yang, Anna Saranti, Alessa Angerschmid, Matthew E. Taylor, Andreas Holzinger:
Human-in-the-Loop Reinforcement Learning: A Survey and Position on Requirements, Challenges, and Opportunities. J. Artif. Intell. Res. 79: 359-415 (2024) - Brittany Davis Pierson, Dustin Arendt, John Miller, Matthew E. Taylor:
Comparing explanations in RL. Neural Comput. Appl. 36(1): 505-516 (2024) - James Reed, Kartik Naik, Andrew Abney, Dillon Herbert, Jacob B. Fine, Ashwin Vadlamannati, James Morris, Trip Taylor, Michael Muglia, Kenneth Granlund, Matthew Bryant, Chris Vermillion:
Experimental Validation of an Iterative Learning-Based Flight Trajectory Optimizer for an Underwater Kite. IEEE Trans. Control. Syst. Technol. 32(4): 1240-1253 (2024) - Andreas Züfle, Flora D. Salim, Taylor Anderson, Matthew Scotch, Li Xiong, Kacper Sokol, Hao Xue, Ruochen Kong, David J. Heslop, Hye-Young Paik, C. Raina MacIntyre:
Leveraging Simulation Data to Understand Bias in Predictive Models of Infectious Disease Spread. ACM Trans. Spatial Algorithms Syst. 10(2): 17 (2024) - Jizhou Wu, Jianye Hao, Tianpei Yang, Xiaotian Hao, Yan Zheng, Weixun Wang, Matthew E. Taylor:
PORTAL: Automatic Curricula Generation for Multiagent Reinforcement Learning. AAAI 2024: 15934-15942 - Tianpei Yang, Heng You, Jianye Hao, Yan Zheng, Matthew E. Taylor:
A Transfer Approach Using Graph Neural Networks in Deep Reinforcement Learning. AAAI 2024: 16352-16360 - Bram Grooten, Tristan Tomilin, Gautham Vasan, Matthew E. Taylor, A. Rupam Mahmood, Meng Fang, Mykola Pechenizkiy, Decebal Constantin Mocanu:
MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning. AAMAS 2024: 733-742 - Chaitanya Kharyal, Sai Krishna Gottipati, Tanmay Kumar Sinha, Srijita Das, Matthew E. Taylor:
GLIDE-RL: Grounded Language Instruction through DEmonstration in RL. AAMAS 2024: 2333-2335 - Calarina Muslimani, Matthew E. Taylor:
Leveraging Sub-Optimal Data for Human-in-the-Loop Reinforcement Learning. AAMAS 2024: 2399-2401 - Simone Parisi, Montaser Mohammedalamen, Alireza Kazemipour, Matthew E. Taylor, Michael Bowling:
Monitored Markov Decision Processes. AAMAS 2024: 1549-1557 - Hao Zhang, Tianpei Yang, Yan Zheng, Jianye Hao, Matthew E. Taylor:
PADDLE: Logic Program Guided Policy Reuse in Deep Reinforcement Learning. AAMAS 2024: 2585-2587 - Stephanie M. Lukin, Claire Bonial, Matthew Marge, Taylor Hudson, Cory J. Hayes, Kimberly A. Pollard, Anthony Baker, Ashley N. Foots, Ron Artstein, Felix Gervits, Mitchell Abrams, Cassidy Henry, Lucia Donatelli, Anton Leuski, Susan G. Hill, David R. Traum, Clare R. Voss:
SCOUT: A Situated and Multi-Modal Human-Robot Dialogue Corpus. LREC/COLING 2024: 14445-14458 - John Niroula, Matthew A. Taylor, Qingyun Xie, Pradyot Yadav, Shisong Luo, Yuji Zhao, Tomás Palacios:
Record High Temperature Performance in Scaled AlGaN/GaN-on-Si HEMTs up to 500°C. DRC 2024: 1-2 - Salvador Medina, Sarah L. Taylor, Carsten Stoll, Gareth Edwards, Alex Hauptmann, Shinji Watanabe, Iain A. Matthews:
PhISANet: Phonetically Informed Speech Animation Network. ICASSP 2024: 8225-8229 - Pablo Laso, Stefano Cerri, Annabel Sorby-Adams, Jennifer Guo, Farrah Mateen, Philipp Goebl, Jiaming Wu, Peirong Liu, Hongwei Bran Li, Sean I. Young, Benjamin Billot, Oula Puonti, Gordon Sze, Sam Payabavash, Adam DeHavenon, Kevin N. Sheth, Matthew S. Rosen, John Kirsch, Nicola Strisciuglio, Jelmer M. Wolterink, Arman Eshaghi, Frederik Barkhof, W. Taylor Kimberly, Juan Eugenio Iglesias:
Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI. ISBI 2024: 1-5 - Raechel Walker, Olivia Dias, Matthew E. Taylor, Cynthia Breazeal:
Alleviating the Danger Of A Single Story Through Liberatory Computing Education. RESPECT 2024: 169-178 - Vincent Serritella, Viktor Lundqvist, Matthew Webb, Taylor Shaw, Riley Niu, Zach Repasky, Robert Graf, Magnus Wrenninge:
A Procedural Production System for Autonomous Vehicle Simulation. SIGGRAPH Talks 2024: 65 - Qianxi Li, Yingyue Cao, Jikun Kang, Tianpei Yang, Xi Chen, Jun Jin, Matthew E. Taylor:
LaFFi: Leveraging Hybrid Natural Language Feedback for Fine-tuning Language Models. CoRR abs/2401.00907 (2024) - Chaitanya Kharyal, Sai Krishna Gottipati, Tanmay Kumar Sinha, Srijita Das, Matthew E. Taylor:
GLIDE-RL: Grounded Language Instruction through DEmonstration in RL. CoRR abs/2401.02991 (2024) - Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Matthew P. Lungren, Maria Wetscherek, Noel Codella, Stephanie L. Hyland, Javier Alvarez-Valle, Ozan Oktay:
RAD-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision. CoRR abs/2401.10815 (2024) - Simone Parisi, Montaser Mohammedalamen, Alireza Kazemipour, Matthew E. Taylor, Michael Bowling:
Monitored Markov Decision Processes. CoRR abs/2402.06819 (2024) - Jean-Paul Ainam, Erim Yanik, Rahul Rahul, Taylor Kunkes, Lora Cavuoto, Brian Clemency, Kaori Tanaka, Matthew Hackett, Jack Norfleet, Suvranu De:
Deep Learning for Video-Based Assessment of Endotracheal Intubation Skills. CoRR abs/2404.11727 (2024) - Shang Wang, Deepak Ranganatha Sastry Mamillapalli, Tianpei Yang, Matthew E. Taylor:
FPGA Divide-and-Conquer Placement using Deep Reinforcement Learning. CoRR abs/2404.13061 (2024) - Daniel May, Matthew Taylor, Petr Musilek:
Decentralized Coordination of Distributed Energy Resources through Local Energy Markets and Deep Reinforcement Learning. CoRR abs/2404.13142 (2024) - Calarina Muslimani, Matthew E. Taylor:
Leveraging Sub-Optimal Data for Human-in-the-Loop Reinforcement Learning. CoRR abs/2405.00746 (2024) - Jonathan Windle, Iain A. Matthews, Sarah Taylor:
LLAniMAtion: LLAMA Driven Gesture Animation. CoRR abs/2405.08042 (2024) - Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Anton Schwaighofer, Sam Bond-Taylor, Maximilian Ilse, Fernando Pérez-García, Valentina Salvatelli, Harshita Sharma, Felix Meissen, Mercy Ranjit, Shaury Srivastav, Julia Gong, Fabian Falck, Ozan Oktay, Anja Thieme, Matthew P. Lungren, Maria Teodora Wetscherek, Javier Alvarez-Valle, Stephanie L. Hyland:
MAIRA-2: Grounded Radiology Report Generation. CoRR abs/2406.04449 (2024) - Calarina Muslimani, Bram Grooten, Deepak Ranganatha Sastry Mamillapalli, Mykola Pechenizkiy, Decebal Constantin Mocanu, Matthew E. Taylor:
Boosting Robustness in Preference-Based Reinforcement Learning with Dynamic Sparsity. CoRR abs/2406.06495 (2024) - Jerson Francia, Derek Hansen, Benjamin L. Schooley, Matthew Taylor, Shydra Murray, Greg Snow:
Assessing AI vs Human-Authored Spear Phishing SMS Attacks: An Empirical Study Using the TRAPD Method. CoRR abs/2406.13049 (2024) - Matthew T. Dearing, Yiheng Tao, Xingfu Wu, Zhiling Lan, Valerie Taylor:
LASSI: An LLM-based Automated Self-Correcting Pipeline for Translating Parallel Scientific Codes. CoRR abs/2407.01638 (2024)
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