no code implementations • 12 Feb 2021 • Alexander Deisting, Abigail Victoria Waldron, Edward Atkin, Gary Barker, Anastasia Basharina-Freshville, Christopher Betancourt, Steven Boyd, Dominic Brailsford, Zachary Chen-Wishart, Linda Cremonesi, Adriana Dias, Patrick Dunne, Jennifer Haigh, Philip Hamacher-Baumann, Sebastian Jones, Asher Kaboth, Alexander Korzenev, William Ma, Philippe Mermod, Maria Mironova, Jocelyn Monroe, Ryan Nichol, Toby Nonnenmacher, Jaroslaw Nowak, William Parker, Harrison Ritchie-Yates, Stefan Roth, Ruben Saakyan, Nicola Serra, Yuri Shitov, Jochen Steinmann, Adam Tarrant, Melissa Uchida, Sammy Valder, Mark Ward, Morgan Wascko
Measurements of proton-nucleus scattering and high resolution neutrino-nucleus interaction imaging are key to reduce neutrino oscillation systematic uncertainties in future experiments.
Instrumentation and Detectors High Energy Physics - Experiment
1 code implementation • 8 Sep 2019 • Prithviraj Ammanabrolu, Ethan Tien, Wesley Cheung, Zhaochen Luo, William Ma, Lara J. Martin, Mark O. Riedl
Neural network based approaches to automated story plot generation attempt to learn how to generate novel plots from a corpus of natural language plot summaries.
Ranked #1 on Event Expansion on Scifi TV Shows
no code implementations • WS 2019 • Prithviraj Ammanabrolu, Ethan Tien, Wesley Cheung, Zhaochen Luo, William Ma, Lara Martin, Mark Riedl
Prior work has shown that a semantic abstraction of sentences called events improves neural plot generation and and allows one to decompose the problem into: (1) the generation of a sequence of events (event-to-event) and (2) the transformation of these events into natural language sentences (event-to-sentence).
2 code implementations • 20 Sep 2018 • A. Rupam Mahmood, Dmytro Korenkevych, Gautham Vasan, William Ma, James Bergstra
The research community is now able to reproduce, analyze and build quickly on these results due to open source implementations of learning algorithms and simulated benchmark tasks.