2 code implementations • 12 Jul 2024 • Polina Turishcheva, Paul G. Fahey, Michaela Vystrčilová, Laura Hansel, Rachel Froebe, Kayla Ponder, Yongrong Qiu, Konstantin F. Willeke, Mohammad Bashiri, Ruslan Baikulov, Yu Zhu, Lei Ma, Shan Yu, Tiejun Huang, Bryan M. Li, Wolf De Wulf, Nina Kudryashova, Matthias H. Hennig, Nathalie L. Rochefort, Arno Onken, Eric Wang, Zhiwei Ding, Andreas S. Tolias, Fabian H. Sinz, Alexander S Ecker
To address this gap, we established the Sensorium 2023 Benchmark Competition with dynamic input, featuring a new large-scale dataset from the primary visual cortex of ten mice.
no code implementations • 10 Jun 2024 • Juan Manuel Zambrano Chaves, Eric Wang, Tao Tu, Eeshit Dhaval Vaishnav, Byron Lee, S. Sara Mahdavi, Christopher Semturs, David Fleet, Vivek Natarajan, Shekoofeh Azizi
Developing therapeutics is a lengthy and expensive process that requires the satisfaction of many different criteria, and AI models capable of expediting the process would be invaluable.
no code implementations • 12 May 2024 • Kareem Ahmed, Stefano Teso, Paolo Morettin, Luca Di Liello, Pierfrancesco Ardino, Jacopo Gobbi, Yitao Liang, Eric Wang, Kai-Wei Chang, Andrea Passerini, Guy Van Den Broeck
We discuss the semantic loss, which injects knowledge about such structure, defined symbolically, into training by minimizing the network's violation of such dependencies, steering the network towards predicting distributions satisfying the underlying structure.
no code implementations • 6 May 2024 • Lin Yang, Shawn Xu, Andrew Sellergren, Timo Kohlberger, Yuchen Zhou, Ira Ktena, Atilla Kiraly, Faruk Ahmed, Farhad Hormozdiari, Tiam Jaroensri, Eric Wang, Ellery Wulczyn, Fayaz Jamil, Theo Guidroz, Chuck Lau, Siyuan Qiao, Yun Liu, Akshay Goel, Kendall Park, Arnav Agharwal, Nick George, Yang Wang, Ryutaro Tanno, David G. T. Barrett, Wei-Hung Weng, S. Sara Mahdavi, Khaled Saab, Tao Tu, Sreenivasa Raju Kalidindi, Mozziyar Etemadi, Jorge Cuadros, Gregory Sorensen, Yossi Matias, Katherine Chou, Greg Corrado, Joelle Barral, Shravya Shetty, David Fleet, S. M. Ali Eslami, Daniel Tse, Shruthi Prabhakara, Cory McLean, Dave Steiner, Rory Pilgrim, Christopher Kelly, Shekoofeh Azizi, Daniel Golden
Building upon Gemini's multimodal models, we develop several models within the new Med-Gemini family that inherit core capabilities of Gemini and are optimized for medical use via fine-tuning with 2D and 3D radiology, histopathology, ophthalmology, dermatology and genomic data.
no code implementations • 20 Apr 2024 • Dave Kleidermacher, Emmanuel Arriaga, Eric Wang, Sebastian Porst, Roger Piqueras Jover
In this paper, we explore the challenges of ensuring security and privacy for users from diverse demographic backgrounds.
1 code implementation • 30 Jan 2024 • Joel Hayford, Jacob Goldman-Wetzler, Eric Wang, Lu Lu
Scientific machine learning (SciML) has emerged as a versatile approach to address complex computational science and engineering problems.
3 code implementations • 31 May 2023 • Polina Turishcheva, Paul G. Fahey, Laura Hansel, Rachel Froebe, Kayla Ponder, Michaela Vystrčilová, Konstantin F. Willeke, Mohammad Bashiri, Eric Wang, Zhiwei Ding, Andreas S. Tolias, Fabian H. Sinz, Alexander S. Ecker
We hope this competition will continue to strengthen the accompanying Sensorium benchmarks collection as a standard tool to measure progress in large-scale neural system identification models of the entire mouse visual hierarchy and beyond.
no code implementations • 7 Dec 2022 • Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger Grosse
Variational autoencoders (VAEs) are powerful tools for learning latent representations of data used in a wide range of applications.
no code implementations • 25 Jan 2022 • Kareem Ahmed, Eric Wang, Kai-Wei Chang, Guy Van Den Broeck
We propose a loss, neuro-symbolic entropy regularization, that encourages the model to confidently predict a valid object.
1 code implementation • 21 May 2021 • Eric Wang, Pasha Khosravi, Guy Van Den Broeck
Understanding the behavior of learned classifiers is an important task, and various black-box explanations, logical reasoning approaches, and model-specific methods have been proposed.
no code implementations • 20 Mar 2021 • Kareem Ahmed, Eric Wang, Guy Van Den Broeck, Kai-Wei Chang
We study the problem of entity-relation extraction in the presence of symbolic domain knowledge.
no code implementations • ICLR 2021 • Konstantin-Klemens Lurz, Mohammad Bashiri, Konstantin Willeke, Akshay Jagadish, Eric Wang, Edgar Y. Walker, Santiago A Cadena, Taliah Muhammad, Erick Cobos, Andreas S. Tolias, Alexander S Ecker, Fabian H. Sinz
With this new readout we train our network on neural responses from mouse primary visual cortex (V1) and obtain a gain in performance of 7% compared to the previous state-of-the-art network.
1 code implementation • ICLR 2019 • Aditya Grover, Eric Wang, Aaron Zweig, Stefano Ermon
Sorting input objects is an important step in many machine learning pipelines.
no code implementations • 11 Feb 2015 • Karl Ni, Roger Pearce, Kofi Boakye, Brian Van Essen, Damian Borth, Barry Chen, Eric Wang
We train our three-layer deep neural network on the Yahoo!
no code implementations • NeurIPS 2010 • Eric Wang, Dehong Liu, Jorge Silva, Lawrence Carin, David B. Dunson
An objective of such analysis is to infer structure and inter-relationships underlying the matrices, here defined by latent features associated with each axis of the matrix.