Computing Depth Contours with Graphics Hardware. - Craig Gotsman; Ian Fischer (CCCG, 2006)

Fast Approximation of High-Order Voronoi Diagrams and Distance Transforms on the GPU. - Ian Fischer; Craig Gotsman (J. Graph. Tools, 2006)

The Emperor's New Security Indicators. - Stuart E. Schechter; Rachna Dhamija; Andy Ozment; Ian Fischer (S&P, 2007)

Cloud Data Protection for the Masses. - Dawn Song; Elaine Shi; Ian Fischer; Umesh Shankar (Computer, 2012)

Speed/Accuracy Trade-Offs for Modern Convolutional Object Detectors. - Jonathan Huang; Vivek Rathod; Chen Sun 002; Menglong Zhu; Anoop Korattikara; Alireza Fathi; Ian Fischer; Zbigniew Wojna; Yang Song 009; Sergio Guadarrama; Kevin Murphy 002 (CVPR, 2017)

Deep Variational Information Bottleneck. - Alexander A. Alemi; Ian Fischer; Joshua V. Dillon; Kevin Murphy 002 (ICLR (Poster), 2017)

Adversarial Transformation Networks: Learning to Generate Adversarial Examples. - Shumeet Baluja; Ian Fischer (CoRR, 2017)

An Information-Theoretic Analysis of Deep Latent-Variable Models. - Alexander A. Alemi; Ben Poole; Ian Fischer; Joshua V. Dillon; Rif A. Saurous; Kevin Murphy 002 (CoRR, 2017)

Learning to Attack: Adversarial Transformation Networks. - Shumeet Baluja; Ian Fischer (AAAI, 2018)

Generative Models of Visually Grounded Imagination. - Ramakrishna Vedantam; Ian Fischer; Jonathan Huang; Kevin Murphy 002 (ICLR (Poster), 2018)

Fixing a Broken ELBO. - Alexander A. Alemi; Ben Poole; Ian Fischer; Joshua V. Dillon; Rif A. Saurous; Kevin Murphy 002 (ICML, 2018)

GILBO: One Metric to Measure Them All. - Alexander A. Alemi; Ian Fischer (NeurIPS, 2018)

Adversarial Examples for Generative Models. - Jernej Kos; Ian Fischer; Dawn Song (IEEE Symposium on Security and Privacy Workshops, 2018)

Uncertainty in the Variational Information Bottleneck. - Alexander A. Alemi; Ian Fischer; Joshua V. Dillon (CoRR, 2018)

TherML: Thermodynamics of Machine Learning. - Alexander A. Alemi; Ian Fischer (CoRR, 2018)

Learning Latent Dynamics for Planning from Pixels. - Danijar Hafner; Timothy P. Lillicrap; Ian Fischer; Ruben Villegas; David Ha; Honglak Lee; James Davidson (ICML, 2019)

Dueling Decoders: Regularizing Variational Autoencoder Latent Spaces. - Bryan Seybold; Emily Fertig; Alex Alemi; Ian Fischer (CoRR, 2019)

An Unsupervised Information-Theoretic Perceptual Quality Metric. - Sangnie Bhardwaj; Ian Fischer; Johannes Ballé; Troy T. Chinen (NeurIPS, 2020)

Predictive Information Accelerates Learning in RL. - Kuang-Huei Lee; Ian Fischer; Anthony Z. Liu; Yijie Guo; Honglak Lee; John F. Canny; Sergio Guadarrama (NeurIPS, 2020)

Information-Bottleneck Approach to Salient Region Discovery. - Andrey Zhmoginov; Ian Fischer; Mark Sandler 002 (ECML/PKDD (3), 2020)

Cycles in Causal Learning. - Katie Everett; Ian Fischer (CoRR, 2020)

VIB is Half Bayes. - Alexander A. Alemi; Warren R. Morningstar; Ben Poole; Ian Fischer; Joshua V. Dillon (CoRR, 2020)

CEB Improves Model Robustness. - Ian Fischer; Alexander A. Alemi (Entropy, 2020)

An Empirical Investigation of Representation Learning for Imitation. - Cynthia Chen; Xin Chen; Sam Toyer; Cody Wild; Scott Emmons; Ian Fischer; Kuang-Huei Lee; Neel Alex; Steven H. Wang; Ping Luo; Stuart Russell 001; Pieter Abbeel; et al. (NeurIPS Datasets and Benchmarks, 2021)

Compressive Visual Representations. - Kuang-Huei Lee; Anurag Arnab; Sergio Guadarrama; John F. Canny; Ian Fischer (NeurIPS, 2021)

PI-QT-Opt: Predictive Information Improves Multi-Task Robotic Reinforcement Learning at Scale. - Kuang-Huei Lee; Ted Xiao; Adrian Li; Paul Wohlhart; Ian Fischer; Yao Lu 006 (CoRL, 2022)

Deep Hierarchical Planning from Pixels. - Danijar Hafner; Kuang-Huei Lee; Ian Fischer; Pieter Abbeel (NeurIPS, 2022)

Multi-Game Decision Transformers. - Kuang-Huei Lee; Ofir Nachum; Mengjiao Yang 001; Lisa Lee; Daniel Freeman; Sergio Guadarrama; Ian Fischer; Winnie Xu; Eric Jang; Henryk Michalewski; Igor Mordatch (NeurIPS, 2022)

An Empirical Investigation of Representation Learning for Imitation. - Xin Chen; Sam Toyer; Cody Wild; Scott Emmons; Ian Fischer; Kuang-Huei Lee; Neel Alex; Steven H. Wang; Ping Luo; Stuart Russell 001; Pieter Abbeel; Rohin Shah (CoRR, 2022)

Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck. - Anirban Samaddar; Sandeep Madireddy; Prasanna Balaprakash; Taps Maiti; Gustavo de los Campos; Ian Fischer (AISTATS, 2023)

Weighted Ensemble Self-Supervised Learning. - Yangjun Ruan; Saurabh Singh; Warren Richard Morningstar; Alexander A. Alemi; Sergey Ioffe; Ian Fischer; Joshua V. Dillon (ICLR, 2023)

A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts. - Kuang-Huei Lee; Xinyun Chen; Hiroki Furuta; John F. Canny; Ian Fischer (ICML, 2024)

Stochastic Sampling from Deterministic Flow Models. - Saurabh Singh; Ian Fischer (CoRR, 2024)

Evolving Deeper LLM Thinking. - Kuang-Huei Lee; Ian Fischer; Yueh-Hua Wu; Dave Marwood; Shumeet Baluja; Dale Schuurmans; Xinyun Chen (CoRR, 2025)