Predicting genre labels for artist using FreeDB. - James Bergstra; Alexandre Lacoste; Douglas Eck (ISMIR, 2006)

Aggregate features and ADABOOSTfor music classification. - James Bergstra; Norman Casagrande; Dumitru Erhan; Douglas Eck; Balázs Kégl (Mach. Learn., 2006)

An empirical evaluation of deep architectures on problems with many factors of variation. - Hugo Larochelle; Dumitru Erhan; Aaron C. Courville; James Bergstra; Yoshua Bengio (ICML, 2007)

Quadratic Features and Deep Architectures for Chunking. - Joseph P. Turian; James Bergstra; Yoshua Bengio (HLT-NAACL (Short Papers), 2009)

Slow, Decorrelated Features for Pretraining Complex Cell-like Networks. - James Bergstra; Yoshua Bengio (NIPS, 2009)

Scalable Genre and Tag Prediction with Spectral Covariance. - James Bergstra; Michael I. Mandel; Douglas Eck (ISMIR, 2010)

Theano: A CPU and GPU Math Compiler in Python. - James Bergstra; Olivier Breuleux; Frédéric Bastien; Pascal Lamblin; Razvan Pascanu; Guillaume Desjardins; Joseph P. Turian; David Warde-Farley; Yoshua Bengio (SciPy, 2010)

Unsupervised Models of Images by Spikeand-Slab RBMs. - Aaron C. Courville; James Bergstra; Yoshua Bengio (ICML, 2011)

Algorithms for Hyper-Parameter Optimization. - James Bergstra; Rémi Bardenet; Yoshua Bengio; Balázs Kégl (NIPS, 2011)

The Statistical Inefficiency of Sparse Coding for Images (or, One Gabor to Rule them All) - James Bergstra; Aaron C. Courville; Yoshua Bengio (CoRR, 2011)

A Spike and Slab Restricted Boltzmann Machine. - Aaron C. Courville; James Bergstra; Yoshua Bengio (AISTATS, 2011)

Suitability of V1 Energy Models for Object Classification. - James Bergstra; Yoshua Bengio; Jérôme Louradour (Neural Comput., 2011)

Making a Science of Model Search - James Bergstra; Dan Yamins; David D. Cox (CoRR, 2012)

Theano: new features and speed improvements - Frédéric Bastien; Pascal Lamblin; Razvan Pascanu; James Bergstra; Ian J. Goodfellow; Arnaud Bergeron; Nicolas Bouchard; David Warde-Farley; Yoshua Bengio (CoRR, 2012)

Random Search for Hyper-Parameter Optimization. - James Bergstra; Yoshua Bengio (J. Mach. Learn. Res., 2012)

Unsupervised and Transfer Learning Challenge: a Deep Learning Approach. - Grégoire Mesnil; Yann N. Dauphin; Xavier Glorot; Salah Rifai; Yoshua Bengio; Ian J. Goodfellow; Erick Lavoie; Xavier Muller; Guillaume Desjardins; David Warde-Farley; Pascal Vincent; Aaron C. Courville; et al. (ICML Unsupervised and Transfer Learning, 2012)

A Neural Model of Human Image Categorization. - Eric Hunsberger; Peter Blouw; James Bergstra; Chris Eliasmith (CogSci, 2013)

Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures. - James Bergstra; Daniel Yamins; David D. Cox (ICML (1), 2013)

Challenges in Representation Learning: A Report on Three Machine Learning Contests. - Ian J. Goodfellow; Dumitru Erhan; Pierre Luc Carrier; Aaron C. Courville; Mehdi Mirza; Benjamin Hamner; William Cukierski; Yichuan Tang; David Thaler; Dong-Hyun Lee; Yingbo Zhou; Chetan Ramaiah; et al. (ICONIP (3), 2013)

SkData: Data Sets and Algorithm Evaluation Protocols in Python. - James Bergstra; Nicolas Pinto; David D. Cox (SciPy, 2013)

Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms. - James Bergstra; Dan Yamins; David D. Cox (SciPy, 2013)

Hyperparameter Optimization and Boosting for Classifying Facial Expressions: How good can a "Null" Model be? - James Bergstra; David D. Cox (CoRR, 2013)

Pylearn2: a machine learning research library. - Ian J. Goodfellow; David Warde-Farley; Pascal Lamblin; Vincent Dumoulin; Mehdi Mirza; Razvan Pascanu; James Bergstra; Frédéric Bastien; Yoshua Bengio (CoRR, 2013)

Nengo: a Python tool for building large-scale functional brain models. - Trevor Bekolay; James Bergstra; Eric Hunsberger; Travis DeWolf; Terrence C. Stewart; Daniel Rasmussen; Feng-Xuan Choo; Aaron Voelker; Chris Eliasmith (Frontiers Neuroinformatics, 2013)

Hyperopt-Sklearn: Automatic Hyperparameter Configuration for Scikit-Learn. - Brent Komer; James Bergstra; Chris Eliasmith (SciPy, 2014)

Preface. - Andy Terrel; Jonathan Rocher; Stéfan van der Walt; James Bergstra (SciPy, 2014)

The Spike-and-Slab RBM and Extensions to Discrete and Sparse Data Distributions. - Aaron C. Courville; Guillaume Desjardins; James Bergstra; Yoshua Bengio (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Challenges in representation learning: A report on three machine learning contests. - Ian J. Goodfellow; Dumitru Erhan; Pierre Luc Carrier; Aaron C. Courville; Mehdi Mirza; Benjamin Hamner; William Cukierski; Yichuan Tang; David Thaler; Dong-Hyun Lee; Yingbo Zhou; Chetan Ramaiah; et al. (Neural Networks, 2015)

Theano: A Python framework for fast computation of mathematical expressions. - Rami Al-Rfou; Guillaume Alain; Amjad Almahairi; Christof Angermüller; Dzmitry Bahdanau; Nicolas Ballas; Frédéric Bastien; Justin Bayer; Anatoly Belikov; Alexander Belopolsky; Yoshua Bengio; Arnaud Bergeron; et al. (CoRR, 2016)

Benchmarking Reinforcement Learning Algorithms on Real-World Robots. - A. Rupam Mahmood; Dmytro Korenkevych; Gautham Vasan; William Ma; James Bergstra (CoRL, 2018)

Setting up a Reinforcement Learning Task with a Real-World Robot. - A. Rupam Mahmood; Dmytro Korenkevych; Brent J. Komer; James Bergstra (IROS, 2018)

Hyperopt-Sklearn. - Brent Komer; James Bergstra; Chris Eliasmith (Automated Machine Learning, 2019)

Autoregressive Policies for Continuous Control Deep Reinforcement Learning. - Dmytro Korenkevych; A. Rupam Mahmood; Gautham Vasan; James Bergstra (IJCAI, 2019)

Active Perception and Representation for Robotic Manipulation. - Youssef Zaky; Gaurav Paruthi; Bryan P. Tripp; James Bergstra (CoRR, 2020)

A Statistical Guarantee for Representation Transfer in Multitask Imitation Learning. - Bryan Chan; Karime Pereida; James Bergstra (CoRR, 2023)

Revisiting Sparse Rewards for Goal-Reaching Reinforcement Learning. - Gautham Vasan; Yan Wang; Fahim Shahriar; James Bergstra; Martin Jägersand; A. Rupam Mahmood (RLJ, 2024)

Offline-to-online Reinforcement Learning for Image-based Grasping with Scarce Demonstrations. - Bryan Chan; Anson Leung; James Bergstra (CoRR, 2024)