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"Cross-disciplinary research experiences and tips for Graduate School Admissions Panelists"
Panelists: Erin Grant (UC Berkeley) Nadine Chang (CMU) Ruairidh Battleday (Princeton) Sophia Sanborn (UC Berkeley) Nikhil Parthasarathy (NYU)
Author Information
Erin Grant (UC Berkeley)
Ruairidh Battleday (Princeton University)
In my research, I study generalization: how our inference about the novel and unknown is guided by our evolved and encountered past. This entails studying and formalizing generalization and analogical learning in humans, and testing these ideas by using them to create better machine-learning algorithms. More broadly, I am interested in furthering our understanding of cognition and intelligence by uniting insights from high-level theories and ideologies of the brain, mind, and computation.
Sophia Sanborn (UC Berkeley)
Nadine Chang (Carnegie Mellon University)
Nikhil Parthasarathy (New York University)
More from the Same Authors
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2021 : Meta-learning inductive biases of learning systems with Gaussian processes »
Michael Li · Erin Grant · Tom Griffiths -
2022 : Panel »
Erin Grant · Richard Turner · Neil Houlsby · Priyanka Agrawal · Abhijeet Awasthi · Salomey Osei -
2022 Workshop: Symmetry and Geometry in Neural Representations (NeurReps) »
Sophia Sanborn · Christian A Shewmake · Simone Azeglio · Arianna Di Bernardo · Nina Miolane -
2022 : Opening Remarks »
Sophia Sanborn -
2022 : Attention as Interpretable Information Processing in Machine Learning Systems »
Erin Grant -
2021 Workshop: 5th Workshop on Meta-Learning »
Erin Grant · Fábio Ferreira · Frank Hutter · Jonathan Richard Schwarz · Joaquin Vanschoren · Huaxiu Yao -
2021 Oral: Passive attention in artificial neural networks predicts human visual selectivity »
Thomas Langlois · Haicheng Zhao · Erin Grant · Ishita Dasgupta · Tom Griffiths · Nori Jacoby -
2021 Poster: Passive attention in artificial neural networks predicts human visual selectivity »
Thomas Langlois · Haicheng Zhao · Erin Grant · Ishita Dasgupta · Tom Griffiths · Nori Jacoby -
2020 : Introduction for invited speaker, Kate Rakelly »
Erin Grant -
2020 : Introduction for invited speaker, Fei-Fei Li »
Erin Grant -
2020 Workshop: Meta-Learning »
Jane Wang · Joaquin Vanschoren · Erin Grant · Jonathan Richard Schwarz · Francesco Visin · Jeff Clune · Roberto Calandra -
2020 : Opening remarks from the WiML 2020 Organizers »
Xinyi Chen · Erin Grant -
2020 Affinity Workshop: Women in Machine Learning »
Xinyi Chen · Erin Grant · Kristy Choi · Krystal Maughan · Xenia Miscouridou · Judy Hanwen Shen · Raquel Aoki · Belén Saldías · Mel Woghiren · Elizabeth Wood -
2019 : Poster Session »
Matthia Sabatelli · Adam Stooke · Amir Abdi · Paulo Rauber · Leonard Adolphs · Ian Osband · Hardik Meisheri · Karol Kurach · Johannes Ackermann · Matt Benatan · GUO ZHANG · Chen Tessler · Dinghan Shen · Mikayel Samvelyan · Riashat Islam · Murtaza Dalal · Luke Harries · Andrey Kurenkov · Konrad Żołna · Sudeep Dasari · Kristian Hartikainen · Ofir Nachum · Kimin Lee · Markus Holzleitner · Vu Nguyen · Francis Song · Christopher Grimm · Felipe Leno da Silva · Yuping Luo · Yifan Wu · Alex Lee · Thomas Paine · Wei-Yang Qu · Daniel Graves · Yannis Flet-Berliac · Yunhao Tang · Suraj Nair · Matthew Hausknecht · Akhil Bagaria · Simon Schmitt · Bowen Baker · Paavo Parmas · Benjamin Eysenbach · Lisa Lee · Siyu Lin · Daniel Seita · Abhishek Gupta · Riley Simmons-Edler · Yijie Guo · Kevin Corder · Vikash Kumar · Scott Fujimoto · Adam Lerer · Ignasi Clavera Gilaberte · Nicholas Rhinehart · Ashvin Nair · Ge Yang · Lingxiao Wang · Sungryull Sohn · J. Fernando Hernandez-Garcia · Xian Yeow Lee · Rupesh Srivastava · Khimya Khetarpal · Chenjun Xiao · Luckeciano Carvalho Melo · Rishabh Agarwal · Tianhe Yu · Glen Berseth · Devendra Singh Chaplot · Jie Tang · Anirudh Srinivasan · Tharun Kumar Reddy Medini · Aaron Havens · Misha Laskin · Asier Mujika · Rohan Saphal · Joseph Marino · Alex Ray · Joshua Achiam · Ajay Mandlekar · Zhuang Liu · Danijar Hafner · Zhiwen Tang · Ted Xiao · Michael Walton · Jeff Druce · Ferran Alet · Zhang-Wei Hong · Stephanie Chan · Anusha Nagabandi · Hao Liu · Hao Sun · Ge Liu · Dinesh Jayaraman · John Co-Reyes · Sophia Sanborn -
2019 : Poster Session #1 »
Adarsh Jamadandi · Sophia Sanborn · Huaxiu Yao · Chen Cai · Yu Chen · Jean-Marc Andreoli · Niklas Stoehr · Shih-Yang Su · Tony Duan · Fábio Ferreira · Davide Belli · Amit Boyarski · Ze Ye · Elahe Ghalebi · Arindam Sarkar · MAHMOUD KHADEMI · Evgeniy Faerman · Joey Bose · Jiaqi Ma · Lin Meng · Seyed Mehran Kazemi · Guangtao Wang · Tong Wu · Yuexin Wu · Chaitanya K. Joshi · Marc Brockschmidt · Daniele Zambon · Colin Graber · Rafaël Van Belle · Osman Asif Malik · Xavier Glorot · Mario Krenn · Chris Cameron · Binxuan Huang · George Stoica · Alexia Toumpa -
2019 : CIFAR-10H: using human-derived soft-label distributions to support more robust and generalizable classification »
Ruairidh Battleday -
2019 : Taxonomic structure in learning from few positive examples »
Erin Grant -
2019 : Meta-learning as hierarchical modeling »
Erin Grant -
2019 Poster: Reconciling meta-learning and continual learning with online mixtures of tasks »
Ghassen Jerfel · Erin Grant · Tom Griffiths · Katherine Heller -
2019 Spotlight: Reconciling meta-learning and continual learning with online mixtures of tasks »
Ghassen Jerfel · Erin Grant · Tom Griffiths · Katherine Heller -
2018 Workshop: NIPS 2018 Workshop on Meta-Learning »
Joaquin Vanschoren · Frank Hutter · Sachin Ravi · Jane Wang · Erin Grant -
2017 : POSTER: Concept acquisition through meta-learning »
Erin Grant