1 code implementation • LTEDI (ACL) 2022 • Kyle Swanson, Joy Hsu, Mirac Suzgun
Using a dataset of Reddit posts that exhibit stress, we demonstrate the ability of our MCTS algorithm to identify interpretable explanations for a person's feeling of stress in both a context-dependent and context-independent manner.
no code implementations • 12 Mar 2021 • Angeliki V. Katsenou, Fan Zhang, Kyle Swanson, Mariana Afonso, Joel Sole, David R. Bull
In HTTP Adaptive Streaming, video content is conventionally encoded by adapting its spatial resolution and quantization level to best match the prevailing network state and display characteristics.
1 code implementation • ACL 2020 • Kyle Swanson, Lili Yu, Tao Lei
Selecting input features of top relevance has become a popular method for building self-explaining models.
1 code implementation • 20 May 2020 • Lior Hirschfeld, Kyle Swanson, Kevin Yang, Regina Barzilay, Connor W. Coley
While we believe these results show that existing UQ methods are not sufficient for all common use-cases and demonstrate the benefits of further research, we conclude with a practical recommendation as to which existing techniques seem to perform well relative to others.
2 code implementations • ICML 2020 • Kevin Yang, Wengong Jin, Kyle Swanson, Regina Barzilay, Tommi Jaakkola
The property predictor is then used as a likelihood model for filtering candidate structures from the generative model.
no code implementations • 25 Sep 2019 • Kevin Yang, Wengong Jin, Kyle Swanson, Regina Barzilay, Tommi Jaakkola
Many challenging prediction problems, from molecular optimization to program synthesis, involve creating complex structured objects as outputs.
no code implementations • 10 Sep 2019 • Kirk Swanson, Shubhendu Trivedi, Joshua Lequieu, Kyle Swanson, Risi Kondor
The characterization of amorphous materials is especially challenging because their lack of long-range order makes it difficult to define structural metrics.
no code implementations • WS 2019 • Kyle Swanson, Lili Yu, Christopher Fox, Jeremy Wohlwend, Tao Lei
Response suggestion is an important task for building human-computer conversation systems.
4 code implementations • 2 Apr 2019 • Kevin Yang, Kyle Swanson, Wengong Jin, Connor Coley, Philipp Eiden, Hua Gao, Angel Guzman-Perez, Timothy Hopper, Brian Kelley, Miriam Mathea, Andrew Palmer, Volker Settels, Tommi Jaakkola, Klavs Jensen, Regina Barzilay
In addition, we introduce a graph convolutional model that consistently matches or outperforms models using fixed molecular descriptors as well as previous graph neural architectures on both public and proprietary datasets.
Ranked #3 on Molecular Property Prediction on QM9