Timezone: »
Live Intro
Mateusz Malinowski · Viorica Patraucean · Grzegorz Swirszcz · Sindy Löwe · Anna Choromanska · Marco Gori · Yanping Huang
Sat Dec 12 06:00 AM -- 06:15 AM (PST) @
Author Information
Mateusz Malinowski (DeepMind)
Mateusz Malinowski is a research scientist at DeepMind, where he works at the intersection of computer vision, natural language understanding, and deep learning. He was granted PhD (Dr.-Ing.) with the highest honor (summa cum laude) at Max Planck Institute for Informatics in 2017 in computer vision for his pioneering work on visual question answering, where he proposed the task and developed methods that answer questions about the content of images. Prior to this, he graduated with honors from Saarland University in computer science. Before that, he studied computer science at Wroclaw University in Poland.
Viorica Patraucean (DeepMind)
Grzegorz Swirszcz (DeepMind)
Sindy Löwe (University of Amsterdam)
Anna Choromanska (NYU)
Marco Gori (University of Siena)
Yanping Huang (Google Brain)
More from the Same Authors
-
2021 : LiRo: Benchmark and leaderboard for Romanian language tasks »
Stefan Dumitrescu · Petru Rebeja · Beata Lorincz · Mihaela Gaman · Andrei Avram · Mihai Ilie · Andrei Pruteanu · Adriana Stan · Lorena Rosia · Cristina Iacobescu · Luciana Morogan · George Dima · Gabriel Marchidan · Traian Rebedea · Madalina Chitez · Dani Yogatama · Sebastian Ruder · Radu Tudor Ionescu · Razvan Pascanu · Viorica Patraucean -
2021 : Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data »
Sindy Löwe · David Madras · Richard Zemel · Max Welling -
2022 : Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task »
Jannik Kossen · Cătălina Cangea · Eszter Vértes · Andrew Jaegle · Viorica Patraucean · Ira Ktena · Nenad Tomasev · Danielle Belgrave -
2022 : Knowledge-driven Active Learning »
Gabriele Ciravegna · Frederic Precioso · Marco Gori -
2022 Poster: Mixture-of-Experts with Expert Choice Routing »
Yanqi Zhou · Tao Lei · Hanxiao Liu · Nan Du · Yanping Huang · Vincent Zhao · Andrew Dai · zhifeng Chen · Quoc V Le · James Laudon -
2022 Poster: Neural Payoff Machines: Predicting Fair and Stable Payoff Allocations Among Team Members »
Daphne Cornelisse · Thomas Rood · Yoram Bachrach · Mateusz Malinowski · Tal Kachman -
2020 : Panel discussion 2 »
Danielle S Bassett · Yoshua Bengio · Cristina Savin · David Duvenaud · Anna Choromanska · Yanping Huang -
2020 : Introduction: Cristina Savin »
Yanping Huang -
2020 : Introduction: David Duvenaud »
Yanping Huang -
2020 : Introduction: Oral 2.1 and Oral 2.2 »
Viorica Patraucean -
2020 : Introduction: Oral 1.1 and Oral 1.2 »
Viorica Patraucean -
2020 : Introduction: Danielle Bassett »
Anna Choromanska -
2020 : Introduction: Yoshua Bengio »
Anna Choromanska -
2020 : Keynote 2: Marco Gori »
Marco Gori -
2020 : Panel discussion 1 »
Bas Veeling · Olivier Teytaud · Karl Friston · Sindy Löwe · Mateusz Malinowski -
2020 : Introduction: Karl Friston »
Mateusz Malinowski -
2020 : Introduction: Olivier Teytaud »
Sindy Löwe -
2020 : Introduction: Bastiaan Veeling »
Mateusz Malinowski -
2020 Workshop: Beyond BackPropagation: Novel Ideas for Training Neural Architectures »
Mateusz Malinowski · Grzegorz Swirszcz · Viorica Patraucean · Marco Gori · Yanping Huang · Sindy Löwe · Anna Choromanska -
2020 Poster: Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign Dropout »
Zhao Chen · Jiquan Ngiam · Yanping Huang · Thang Luong · Henrik Kretzschmar · Yuning Chai · Dragomir Anguelov -
2019 Poster: Putting An End to End-to-End: Gradient-Isolated Learning of Representations »
Sindy Löwe · Peter O'Connor · Bas Veeling -
2019 Oral: Putting An End to End-to-End: Gradient-Isolated Learning of Representations »
Sindy Löwe · Peter O'Connor · Bas Veeling -
2019 Poster: Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models »
Yunfei Teng · Wenbo Gao · François Chalus · Anna Choromanska · Donald Goldfarb · Adrian Weller -
2019 Poster: GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism »
Yanping Huang · Youlong Cheng · Ankur Bapna · Orhan Firat · Dehao Chen · Mia Chen · HyoukJoong Lee · Jiquan Ngiam · Quoc V Le · Yonghui Wu · zhifeng Chen -
2019 Poster: Learning dynamic polynomial proofs »
Alhussein Fawzi · Mateusz Malinowski · Hamza Fawzi · Omar Fawzi -
2019 Spotlight: Learning dynamic polynomial proofs »
Alhussein Fawzi · Mateusz Malinowski · Hamza Fawzi · Omar Fawzi -
2018 Workshop: Visually grounded interaction and language »
Florian Strub · Harm de Vries · Erik Wijmans · Samyak Datta · Ethan Perez · Mateusz Malinowski · Stefan Lee · Peter Anderson · Aaron Courville · Jeremie MARY · Dhruv Batra · Devi Parikh · Olivier Pietquin · Chiori HORI · Tim Marks · Anoop Cherian -
2018 Poster: Learning to Navigate in Cities Without a Map »
Piotr Mirowski · Matt Grimes · Mateusz Malinowski · Karl Moritz Hermann · Keith Anderson · Denis Teplyashin · Karen Simonyan · koray kavukcuoglu · Andrew Zisserman · Raia Hadsell -
2017 Workshop: Visually grounded interaction and language »
Florian Strub · Harm de Vries · Abhishek Das · Satwik Kottur · Stefan Lee · Mateusz Malinowski · Olivier Pietquin · Devi Parikh · Dhruv Batra · Aaron Courville · Jeremie Mary -
2017 Poster: A simple neural network module for relational reasoning »
Adam Santoro · David Raposo · David Barrett · Mateusz Malinowski · Razvan Pascanu · Peter Battaglia · Timothy Lillicrap -
2017 Spotlight: A simple neural network module for relational reasoning »
Adam Santoro · David Raposo · David Barrett · Mateusz Malinowski · Razvan Pascanu · Peter Battaglia · Timothy Lillicrap -
2017 Poster: Sobolev Training for Neural Networks »
Wojciech Czarnecki · Simon Osindero · Max Jaderberg · Grzegorz Swirszcz · Razvan Pascanu -
2014 Poster: A Multi-World Approach to Question Answering about Real-World Scenes based on Uncertain Input »
Mateusz Malinowski · Mario Fritz