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Ian Fischer
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2020 – today
- 2024
- [c22]Kuang-Huei Lee, Xinyun Chen, Hiroki Furuta, John F. Canny, Ian Fischer:
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts. ICML 2024 - [i25]Kuang-Huei Lee, Xinyun Chen, Hiroki Furuta, John F. Canny, Ian Fischer:
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts. CoRR abs/2402.09727 (2024) - [i24]Saurabh Singh, Ian Fischer:
Stochastic Sampling from Deterministic Flow Models. CoRR abs/2410.02217 (2024) - 2023
- [c21]Anirban Samaddar, Sandeep Madireddy, Prasanna Balaprakash, Taps Maiti, Gustavo de los Campos, Ian Fischer:
Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck. AISTATS 2023: 10207-10222 - [c20]Yangjun Ruan, Saurabh Singh, Warren Richard Morningstar, Alexander A. Alemi, Sergey Ioffe, Ian Fischer, Joshua V. Dillon:
Weighted Ensemble Self-Supervised Learning. ICLR 2023 - 2022
- [c19]Kuang-Huei Lee, Ted Xiao, Adrian Li, Paul Wohlhart, Ian Fischer, Yao Lu:
PI-QT-Opt: Predictive Information Improves Multi-Task Robotic Reinforcement Learning at Scale. CoRL 2022: 1696-1707 - [c18]Danijar Hafner, Kuang-Huei Lee, Ian Fischer, Pieter Abbeel:
Deep Hierarchical Planning from Pixels. NeurIPS 2022 - [c17]Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang, Lisa Lee, Daniel Freeman, Sergio Guadarrama, Ian Fischer, Winnie Xu, Eric Jang, Henryk Michalewski, Igor Mordatch:
Multi-Game Decision Transformers. NeurIPS 2022 - [i23]Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah:
An Empirical Investigation of Representation Learning for Imitation. CoRR abs/2205.07886 (2022) - [i22]Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang, Lisa Lee, Daniel Freeman, Winnie Xu, Sergio Guadarrama, Ian Fischer, Eric Jang, Henryk Michalewski, Igor Mordatch:
Multi-Game Decision Transformers. CoRR abs/2205.15241 (2022) - [i21]Danijar Hafner, Kuang-Huei Lee, Ian Fischer, Pieter Abbeel:
Deep Hierarchical Planning from Pixels. CoRR abs/2206.04114 (2022) - [i20]Kuang-Huei Lee, Ted Xiao, Adrian Li, Paul Wohlhart, Ian Fischer, Yao Lu:
PI-QT-Opt: Predictive Information Improves Multi-Task Robotic Reinforcement Learning at Scale. CoRR abs/2210.08217 (2022) - [i19]Yangjun Ruan, Saurabh Singh, Warren R. Morningstar, Alexander A. Alemi, Sergey Ioffe, Ian Fischer, Joshua V. Dillon:
Weighted Ensemble Self-Supervised Learning. CoRR abs/2211.09981 (2022) - 2021
- [c16]Cynthia Chen, Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah:
An Empirical Investigation of Representation Learning for Imitation. NeurIPS Datasets and Benchmarks 2021 - [c15]Kuang-Huei Lee, Anurag Arnab, Sergio Guadarrama, John F. Canny, Ian Fischer:
Compressive Visual Representations. NeurIPS 2021: 19538-19552 - [i18]Kuang-Huei Lee, Anurag Arnab, Sergio Guadarrama, John F. Canny, Ian Fischer:
Compressive Visual Representations. CoRR abs/2109.12909 (2021) - 2020
- [j3]Ian Fischer
, Alexander A. Alemi
CEB Improves Model Robustness. Entropy 22(10): 1081 (2020) - [c14]Sangnie Bhardwaj, Ian Fischer, Johannes Ballé, Troy T. Chinen:
An Unsupervised Information-Theoretic Perceptual Quality Metric. NeurIPS 2020 - [c13]Kuang-Huei Lee, Ian Fischer, Anthony Z. Liu, Yijie Guo, Honglak Lee, John F. Canny, Sergio Guadarrama:
Predictive Information Accelerates Learning in RL. NeurIPS 2020 - [c12]Andrey Zhmoginov, Ian Fischer, Mark Sandler:
Information-Bottleneck Approach to Salient Region Discovery. ECML/PKDD (3) 2020: 531-546 - [i17]Ian Fischer, Alexander A. Alemi:
CEB Improves Model Robustness. CoRR abs/2002.05380 (2020) - [i16]Sangnie Bhardwaj, Ian Fischer, Johannes Ballé, Troy T. Chinen:
An Unsupervised Information-Theoretic Perceptual Quality Metric. CoRR abs/2006.06752 (2020) - [i15]Katie Everett, Ian Fischer:
Cycles in Causal Learning. CoRR abs/2007.12335 (2020) - [i14]Kuang-Huei Lee, Ian Fischer, Anthony Z. Liu, Yijie Guo, Honglak Lee, John F. Canny, Sergio Guadarrama:
Predictive Information Accelerates Learning in RL. CoRR abs/2007.12401 (2020) - [i13]Alexander A. Alemi, Warren R. Morningstar, Ben Poole, Ian Fischer, Joshua V. Dillon:
VIB is Half Bayes. CoRR abs/2011.08711 (2020)
2010 – 2019
- 2019
- [c11]Danijar Hafner, Timothy P. Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson:
Learning Latent Dynamics for Planning from Pixels. ICML 2019: 2555-2565 - [i12]Bryan Seybold, Emily Fertig, Alex Alemi, Ian Fischer:
Dueling Decoders: Regularizing Variational Autoencoder Latent Spaces. CoRR abs/1905.07478 (2019) - [i11]Andrey Zhmoginov, Ian Fischer, Mark Sandler:
Information-Bottleneck Approach to Salient Region Discovery. CoRR abs/1907.09578 (2019) - 2018
- [c10]Shumeet Baluja, Ian Fischer:
Learning to Attack: Adversarial Transformation Networks. AAAI 2018: 2687-2695 - [c9]Alexander A. Alemi, Ian Fischer:
GILBO: One Metric to Measure Them All. ICLR (Workshop) 2018 - [c8]Ramakrishna Vedantam, Ian Fischer, Jonathan Huang, Kevin Murphy:
Generative Models of Visually Grounded Imagination. ICLR (Poster) 2018 - [c7]Alexander A. Alemi, Ben Poole, Ian Fischer, Joshua V. Dillon, Rif A. Saurous, Kevin Murphy:
Fixing a Broken ELBO. ICML 2018: 159-168 - [c6]Alexander A. Alemi, Ian Fischer:
GILBO: One Metric to Measure Them All. NeurIPS 2018: 7037-7046 - [c5]Jernej Kos, Ian Fischer, Dawn Song:
Adversarial Examples for Generative Models. IEEE Symposium on Security and Privacy Workshops 2018: 36-42 - [i10]Alexander A. Alemi, Ian Fischer:
GILBO: One Metric to Measure Them All. CoRR abs/1802.04874 (2018) - [i9]Alexander A. Alemi, Ian Fischer, Joshua V. Dillon:
Uncertainty in the Variational Information Bottleneck. CoRR abs/1807.00906 (2018) - [i8]Alexander A. Alemi, Ian Fischer:
TherML: Thermodynamics of Machine Learning. CoRR abs/1807.04162 (2018) - [i7]Danijar Hafner, Timothy P. Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson:
Learning Latent Dynamics for Planning from Pixels. CoRR abs/1811.04551 (2018) - 2017
- [c4]Jonathan Huang, Vivek Rathod, Chen Sun, Menglong Zhu, Anoop Korattikara, Alireza Fathi, Ian Fischer, Zbigniew Wojna
Speed/Accuracy Trade-Offs for Modern Convolutional Object Detectors. CVPR 2017: 3296-3297 - [c3]Alexander A. Alemi, Ian Fischer, Joshua V. Dillon, Kevin Murphy:
Deep Variational Information Bottleneck. ICLR (Poster) 2017 - [i6]Jernej Kos, Ian Fischer, Dawn Song:
Adversarial examples for generative models. CoRR abs/1702.06832 (2017) - [i5]Shumeet Baluja, Ian Fischer:
Adversarial Transformation Networks: Learning to Generate Adversarial Examples. CoRR abs/1703.09387 (2017) - [i4]Ramakrishna Vedantam, Ian Fischer, Jonathan Huang, Kevin Murphy:
Generative Models of Visually Grounded Imagination. CoRR abs/1705.10762 (2017) - [i3]Alexander A. Alemi, Ben Poole, Ian Fischer, Joshua V. Dillon, Rif A. Saurous, Kevin Murphy:
An Information-Theoretic Analysis of Deep Latent-Variable Models. CoRR abs/1711.00464 (2017) - 2016
- [i2]Jonathan Huang, Vivek Rathod, Chen Sun, Menglong Zhu, Anoop Korattikara, Alireza Fathi, Ian Fischer, Zbigniew Wojna, Yang Song, Sergio Guadarrama, Kevin Murphy:
Speed/accuracy trade-offs for modern convolutional object detectors. CoRR abs/1611.10012 (2016) - [i1]Alexander A. Alemi, Ian Fischer, Joshua V. Dillon, Kevin Murphy:
Deep Variational Information Bottleneck. CoRR abs/1612.00410 (2016) - 2012
- [j2]Dawn Song, Elaine Shi, Ian Fischer, Umesh Shankar:
Cloud Data Protection for the Masses. Computer 45(1): 39-45 (2012)
2000 – 2009
- 2007
- [c2]Stuart E. Schechter, Rachna Dhamija, Andy Ozment, Ian Fischer:
The Emperor's New Security Indicators. S&P 2007: 51-65 - 2006
- [j1]Ian Fischer, Craig Gotsman:
Fast Approximation of High-Order Voronoi Diagrams and Distance Transforms on the GPU. J. Graph. Tools 11(4): 39-60 (2006) - [c1]Craig Gotsman, Ian Fischer:
Computing Depth Contours with Graphics Hardware. CCCG 2006
Coauthor Index
aka: Alex Alemi
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