Publications

Christopher Williams, FF, George Deligiannidis, Chris Holmes, Arnaud Doucet, Saifuddin Syed (2023). A Unified Framework for U-Net Design and Analysis. NeurIPS 2023.

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FF, Christopher Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris Holmes, Arnaud Doucet, Matthew Willetts (2022). A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs. NeurIPS 2022 (oral).

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Oscar Clivio, FF, George Deligiannidis, Brieuc Lehmann, Chris Holmes (2022). Neural Score Matching for High-Dimensional Causal Inference. AISTATS 2022 (also presented at American Causal Inference Conference 2022).

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FF, Haoting Zhang, Matthew Willetts, George Nicholson, Christopher Yau, Chris Holmes (2021). Multi-Facet Clustering Variational Autoencoders. NeurIPS 2021.

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Subhrajit Roy, Stephen Pfohl, Girmaw Abebe Tadesse, Luis Oala, FF, Yuyin Zhou, Liyue Shen, Ghada Zamzmi, Purity Mugambi, Ayah Zirikly, Matthew BA McDermott, Emily Alsentzer (2021). Machine Learning for Health (ML4H) 2021. ML4H 2021.

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Xuan Zhu, FF, Sahra Ghalebikesabi, Matthias Kormaksson, Marc Vandemeulebroecke, Cong Zhang, Luis Santos, Chun Hei Kwok, Dominique West, Ann-Marie Mallon, Ruvie Martin, Aimee Readie, Kunal Gandhi, Gregory Ligozio, George Nicholson (2021). Identification of Underlying Disease Domains by Longitudinal Latent Factor Analysis for Secukinumab Treated Patients in Psoriatic Arthritis and Rheumatoid Arthritis Trials. American College of Rheumatology Convergence 2021.

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Daniel Lenton, Fabio Pardo, FF, Stephen James, Ronald Clark (2021). Ivy: Templated Deep Learning for Inter-Framework Portability. Preprint.

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Suproteem K. Sarkar, Subhrajit Roy, Emily Alsentzer, Matthew B. A. McDermott, FF, Ioana Bica, Griffin Adams, Stephen Pfohl, Brett Beaulieu-Jones, Tristan Naumann, Stephanie L. Hyland (2020). Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All. Proceedings of Machine Learning Research.

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FF, Sagar Doshi, Marion Tormento, Gor Nersisyan, Nico Smuts, John Lingi, Kim Rants, Roni Permana Saputra, Ke Wang, Petar Kormushev (2020). Robot DE NIRO: A Human-Centered, Autonomous, Mobile Research Platform for Cognitively-Enhanced Manipulation. Journal Frontiers in Robotics and AI, also at IROS 2019 Workshop Towards Robots that Exhibit Manipulation Intelligence (spotlight & poster).

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Zoe Landgraf, FF, Michael Bloesch, Stefan Leutenegger, Andrew Davison (2020). Comparing View-Based and Map-Based Semantic Labelling in Real-Time SLAM. ICRA 2020 (presentation).

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Adrian V. Dalca, Matthew Mcdermott, Emily Alsentzer, Sam Finlayson, Michael Oberst, FF, Corey Chivers, Andrew L. Beam, Tristan Naumann, Brett Beaulieu-Jones (2019). Machine Learning for Health 2019: What Makes Machine Learning in Medicine Different?. Proceedings of Machine Learning Research.

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Chufan Gao, FF, Mononito Goswami, Michael R. Pinsky, Anthony Wertz, Artur Dubrawski (2019). Detecting Patterns of Physiological Response to Hemodynamic Stress via Unsupervised Deep Learning. NeurIPS 2019 ML4H Workshop.

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FF, Julian Marstaller, Niklas Stoehr, Soeren Maucher, Jeana Ren, Andreas Thalhammer, Achim Rettinger, Rudi Studer (2019). Measuring Proximity between Newspapers and Political Parties – The Sentiment Political Compass. Journal Policy & Internet (presentation), also at The Internet, Policy & Politics Conference, University of Oxford.

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Niklas Stoehr, Luis Sanchez, Daniil Gannota, FF (2019). From Accuracy to Versatility: Analysing Text Classification Models regarding Transfer Learning. IEEE International Workshop on Deep and Transfer Learning.

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FF, Kawin Larppichet, Petar Kormushev (2019). DE VITO: A Dual-arm, High Degree-of-freedom, Lightweight, Inexpensive, Passive Upper-limb Exoskeleton for Robot Teleoperation. 20th Conference Towards Autonomous Robotic Systems (Best Paper Award & presentation).

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FF, Michael R. Pinsky, Gilles Clermont, Artur Dubrawski (2018). Deep Sequence Modeling for Hemorrhage Diagnosis. NeurIPS 2018 ML4H Workshop (spotlight), also at International Symposium on Intensive Care and Emergency Medicine (abstract & poster presentation).

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