Search Results for author: Lucy Colwell

Found 8 papers, 2 papers with code

Meaningful machine learning models and machine-learned pharmacophores from fragment screening campaigns

no code implementations25 Mar 2022 Carl Poelking, Gianni Chessari, Christopher W. Murray, Richard J. Hall, Lucy Colwell, Marcel Verdonk

In this study we derive ML models from over 50 fragment-screening campaigns to introduce two important elements that we believe are absent in most -- if not all -- ML studies of this type reported to date: First, alongside the observed hits we use to train our models, we incorporate true misses and show that these experimentally validated negative data are of significant importance to the quality of the derived models.

BIG-bench Machine Learning Drug Discovery

Rethinking Attention with Performers

11 code implementations ICLR 2021 Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy Colwell, Adrian Weller

We introduce Performers, Transformer architectures which can estimate regular (softmax) full-rank-attention Transformers with provable accuracy, but using only linear (as opposed to quadratic) space and time complexity, without relying on any priors such as sparsity or low-rankness.

Ranked #15 on Image Generation on ImageNet 64x64 (Bits per dim metric)

Image Generation

Attribution Methods Reveal Flaws in Fingerprint-Based Virtual Screening

no code implementations2 Jul 2020 Vikram Sundar, Lucy Colwell

Our results confirm that high-performing models may not learn the correct binding rule, and suggest concrete steps that can remedy this situation.

Population-Based Black-Box Optimization for Biological Sequence Design

no code implementations ICML 2020 Christof Angermueller, David Belanger, Andreea Gane, Zelda Mariet, David Dohan, Kevin Murphy, Lucy Colwell, D. Sculley

The cost and latency of wet-lab experiments requires methods that find good sequences in few experimental rounds of large batches of sequences--a setting that off-the-shelf black-box optimization methods are ill-equipped to handle.

Noisy, sparse, nonlinear: Navigating the Bermuda Triangle of physical inference with deep filtering

no code implementations19 Nov 2019 Carl Poelking, Yehia Amar, Alexei Lapkin, Lucy Colwell

Capturing the microscopic interactions that determine molecular reactivity poses a challenge across the physical sciences.

BIG-bench Machine Learning

Using Attribution to Decode Dataset Bias in Neural Network Models for Chemistry

no code implementations27 Nov 2018 Kevin McCloskey, Ankur Taly, Federico Monti, Michael P. Brenner, Lucy Colwell

The dataset bias makes these models unreliable for accurately revealing information about the mechanisms of protein-ligand binding.

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