How Molecules Impact Cells: Unlocking Contrastive PhenoMolecular Retrieval

no code implementations • 10 Sep 2024 • Philip Fradkin, Puria Azadi, Karush Suri, Frederik Wenkel, Ali Bashashati, Maciej Sypetkowski, Dominique Beaini

Predicting molecular impact on cellular function is a core challenge in therapeutic design.

Contrastive Learning Drug Discovery +1

On the Scalability of GNNs for Molecular Graphs

no code implementations • 17 Apr 2024 • Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei, Nia Dickson, Karush Suri, Philip Fradkin, Dominique Beaini

However, structure-based architectures such as Graph Neural Networks (GNNs) are yet to show the benefits of scale mainly due to the lower efficiency of sparse operations, large data requirements, and lack of clarity about the effectiveness of various architectures.

Diversity Drug Discovery +3

Masked Autoencoders for Microscopy are Scalable Learners of Cellular Biology

1 code implementation • CVPR 2024 • Oren Kraus, Kian Kenyon-Dean, Saber Saberian, Maryam Fallah, Peter McLean, Jess Leung, Vasudev Sharma, Ayla Khan, Jia Balakrishnan, Safiye Celik, Dominique Beaini, Maciej Sypetkowski, Chi Vicky Cheng, Kristen Morse, Maureen Makes, Ben Mabey, Berton Earnshaw

Featurizing microscopy images for use in biological research remains a significant challenge, especially for large-scale experiments spanning millions of images.

Drug Discovery Self-Supervised Learning

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets

1 code implementation • 6 Oct 2023 • Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michał Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Ioannis Koutis, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew Fitzgibbon, Błażej Banaszewski, Chad Martin, Dominic Masters

Recently, pre-trained foundation models have enabled significant advancements in multiple fields.

Masked Autoencoders are Scalable Learners of Cellular Morphology

1 code implementation • 27 Sep 2023 • Oren Kraus, Kian Kenyon-Dean, Saber Saberian, Maryam Fallah, Peter McLean, Jess Leung, Vasudev Sharma, Ayla Khan, Jia Balakrishnan, Safiye Celik, Maciej Sypetkowski, Chi Vicky Cheng, Kristen Morse, Maureen Makes, Ben Mabey, Berton Earnshaw

Inferring biological relationships from cellular phenotypes in high-content microscopy screens provides significant opportunity and challenge in biological research.

Spatial Latent Representations in Generative Adversarial Networks for Image Generation

no code implementations • 25 Mar 2023 • Maciej Sypetkowski

In this work, we define a family of spatial latent spaces for StyleGAN2, capable of capturing more details and representing images that are out-of-sample in terms of the number and arrangement of object parts, such as an image of multiple faces or a face with more than two eyes.

Attribute Image Manipulation

RxRx1: A Dataset for Evaluating Experimental Batch Correction Methods

no code implementations • 13 Jan 2023 • Maciej Sypetkowski, Morteza Rezanejad, Saber Saberian, Oren Kraus, John Urbanik, James Taylor, Ben Mabey, Mason Victors, Jason Yosinski, Alborz Rezazadeh Sereshkeh, Imran Haque, Berton Earnshaw

We propose a classification task designed to evaluate the effectiveness of experimental batch correction methods on these images and examine the performance of a number of correction methods on this task.

Insights From the NeurIPS 2021 NetHack Challenge

1 code implementation • 22 Mar 2022 • Eric Hambro, Sharada Mohanty, Dmitrii Babaev, Minwoo Byeon, Dipam Chakraborty, Edward Grefenstette, Minqi Jiang, DaeJin Jo, Anssi Kanervisto, Jongmin Kim, Sungwoong Kim, Robert Kirk, Vitaly Kurin, Heinrich Küttler, Taehwon Kwon, Donghoon Lee, Vegard Mella, Nantas Nardelli, Ivan Nazarov, Nikita Ovsov, Jack Parker-Holder, Roberta Raileanu, Karolis Ramanauskas, Tim Rocktäschel, Danielle Rothermel, Mikayel Samvelyan, Dmitry Sorokin, Maciej Sypetkowski, Michał Sypetkowski

In this report, we summarize the takeaways from the first NeurIPS 2021 NetHack Challenge.

NetHack Reinforcement Learning (RL)

Augmentation Inside the Network

no code implementations • 19 Dec 2020 • Maciej Sypetkowski, Jakub Jasiulewicz, Zbigniew Wojna

We propose a modification that is 30% faster than the flip test-time augmentation and achieves the same results for CIFAR-100.

Data Augmentation Image Classification