Efficient Learning of Sparse Representations with an Energy-Based Model. - Marc'Aurelio Ranzato; Christopher S. Poultney; Sumit Chopra; Yann LeCun (NIPS, 2006)

Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition. - Marc'Aurelio Ranzato; Fu Jie Huang; Y-Lan Boureau; Yann LeCun (CVPR, 2007)

Energy-Based Models in Document Recognition and Computer Vision. - Yann LeCun; Sumit Chopra; Marc'Aurelio Ranzato; Fu Jie Huang (ICDAR, 2007)

A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images. - Marc'Aurelio Ranzato; Yann LeCun (ICDAR, 2007)

Sparse Feature Learning for Deep Belief Networks. - Marc'Aurelio Ranzato; Y-Lan Boureau; Yann LeCun (NIPS, 2007)

A Unified Energy-Based Framework for Unsupervised Learning. - Marc'Aurelio Ranzato; Y-Lan Boureau; Sumit Chopra; Yann LeCun (AISTATS, 2007)

Automatic recognition of biological particles in microscopic images. - Marc'Aurelio Ranzato; P. E. Taylor; James M. House; R. C. Flagan; Yann LeCun; Pietro Perona (Pattern Recognit. Lett., 2007)

Semi-supervised learning of compact document representations with deep networks. - Marc'Aurelio Ranzato; Martin Szummer (ICML, 2008)

Learning invariant features through topographic filter maps. - Koray Kavukcuoglu; Marc'Aurelio Ranzato; Rob Fergus; Yann LeCun (CVPR, 2009)

What is the best multi-stage architecture for object recognition? - Kevin Jarrett; Koray Kavukcuoglu; Marc'Aurelio Ranzato; Yann LeCun (ICCV, 2009)

Unsupervised image ranking. - Eva Hörster; Malcolm Slaney; Marc'Aurelio Ranzato; Kilian Q. Weinberger (LS-MMRM@ACM Multimedia, 2009)

Unsupervised Learning of Feature Hierarchies. - Marc'Aurelio Ranzato (2009)

Modeling pixel means and covariances using factorized third-order boltzmann machines. - Marc'Aurelio Ranzato; Geoffrey E. Hinton (CVPR, 2010)

Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine. - George E. Dahl; Marc'Aurelio Ranzato; Abdel-rahman Mohamed; Geoffrey E. Hinton (NIPS, 2010)

Generating more realistic images using gated MRF's. - Marc'Aurelio Ranzato; Volodymyr Mnih; Geoffrey E. Hinton (NIPS, 2010)

Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition - Koray Kavukcuoglu; Marc'Aurelio Ranzato; Yann LeCun (CoRR, 2010)

Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images. - Marc'Aurelio Ranzato; Alex Krizhevsky; Geoffrey E. Hinton (AISTATS, 2010)

On deep generative models with applications to recognition. - Marc'Aurelio Ranzato; Joshua M. Susskind; Volodymyr Mnih; Geoffrey E. Hinton (CVPR, 2011)

On Autoencoders and Score Matching for Energy Based Models. - Kevin Swersky; Marc'Aurelio Ranzato; David Buchman; Benjamin M. Marlin; Nando de Freitas (ICML, 2011)

Building high-level features using large scale unsupervised learning. - Quoc V. Le; Marc'Aurelio Ranzato; Rajat Monga; Matthieu Devin; Greg Corrado; Kai Chen 010; Jeffrey Dean; Andrew Y. Ng (ICML, 2012)

Large Scale Distributed Deep Networks. - Jeffrey Dean; Greg Corrado; Rajat Monga; Kai Chen 010; Matthieu Devin; Quoc V. Le; Mark Z. Mao; Marc'Aurelio Ranzato; Andrew W. Senior; Paul A. Tucker; Ke Yang; Andrew Y. Ng (NIPS, 2012)

Multilingual acoustic models using distributed deep neural networks. - Georg Heigold; Vincent Vanhoucke; Andrew W. Senior; Patrick Nguyen; Marc'Aurelio Ranzato; Matthieu Devin; Jeffrey Dean (ICASSP, 2013)

An empirical study of learning rates in deep neural networks for speech recognition. - Andrew W. Senior; Georg Heigold; Marc'Aurelio Ranzato; Ke Yang (ICASSP, 2013)

On rectified linear units for speech processing. - Matthew D. Zeiler; Marc'Aurelio Ranzato; Rajat Monga; Mark Z. Mao; K. Yang; Quoc Viet Le; Patrick Nguyen; Andrew W. Senior; Vincent Vanhoucke; Jeffrey Dean; Geoffrey E. Hinton (ICASSP, 2013)

Predicting Parameters in Deep Learning. - Misha Denil; Babak Shakibi; Laurent Dinh; Marc'Aurelio Ranzato; Nando de Freitas (NIPS, 2013)

DeViSE: A Deep Visual-Semantic Embedding Model. - Andrea Frome; Gregory S. Corrado; Jonathon Shlens; Samy Bengio; Jeffrey Dean; Marc'Aurelio Ranzato; Tomás Mikolov (NIPS, 2013)

Modeling Natural Images Using Gated MRFs. - Marc'Aurelio Ranzato; Volodymyr Mnih; Joshua M. Susskind; Geoffrey E. Hinton (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

DeepFace: Closing the Gap to Human-Level Performance in Face Verification. - Yaniv Taigman; Ming Yang 007; Marc'Aurelio Ranzato; Lior Wolf (CVPR, 2014)

PANDA: Pose Aligned Networks for Deep Attribute Modeling. - Ning Zhang 014; Manohar Paluri; Marc'Aurelio Ranzato; Trevor Darrell; Lubomir D. Bourdev (CVPR, 2014)

Learning Factored Representations in a Deep Mixture of Experts. - David Eigen; Marc'Aurelio Ranzato; Ilya Sutskever (ICLR (Workshop Poster), 2014)

On Learning Where To Look. - Marc'Aurelio Ranzato (CoRR, 2014)

Video (language) modeling: a baseline for generative models of natural videos. - Marc'Aurelio Ranzato; Arthur Szlam; Joan Bruna; Michaël Mathieu; Ronan Collobert; Sumit Chopra (CoRR, 2014)

Multi-GPU Training of ConvNets. - Omry Yadan; Keith Adams; Yaniv Taigman; Marc'Aurelio Ranzato (ICLR (Workshop Poster), 2014)

Web-scale training for face identification. - Yaniv Taigman; Ming Yang 007; Marc'Aurelio Ranzato; Lior Wolf (CVPR, 2015)

Scale-invariant learning and convolutional networks. - Soumith Chintala; Marc'Aurelio Ranzato; Arthur Szlam; Yuandong Tian; Mark Tygert; Wojciech Zaremba (CoRR, 2015)

Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie Reviews. - Grégoire Mesnil; Tomás Mikolov; Marc'Aurelio Ranzato; Yoshua Bengio (ICLR (Workshop), 2015)

Learning Longer Memory in Recurrent Neural Networks. - Tomás Mikolov; Armand Joulin; Sumit Chopra; Michaël Mathieu; Marc'Aurelio Ranzato (ICLR (Workshop), 2015)

Guest Editorial: Deep Learning. - Marc'Aurelio Ranzato; Geoffrey E. Hinton; Yann LeCun (Int. J. Comput. Vis., 2015)

Learning Through Dialogue Interactions. - Jiwei Li; Alexander H. Miller; Sumit Chopra; Marc'Aurelio Ranzato; Jason Weston (CoRR, 2016)

Sequence Level Training with Recurrent Neural Networks. - Marc'Aurelio Ranzato; Sumit Chopra; Michael Auli; Wojciech Zaremba (ICLR (Poster), 2016)

Hard Mixtures of Experts for Large Scale Weakly Supervised Vision. - Sam Gross; Marc'Aurelio Ranzato; Arthur Szlam (CVPR, 2017)

Dialogue Learning With Human-in-the-Loop. - Jiwei Li; Alexander H. Miller; Sumit Chopra; Marc'Aurelio Ranzato; Jason Weston (ICLR (Poster), 2017)

Learning through Dialogue Interactions by Asking Questions. - Jiwei Li; Alexander H. Miller; Sumit Chopra; Marc'Aurelio Ranzato; Jason Weston (ICLR (Poster), 2017)

Fader Networks: Manipulating Images by Sliding Attributes. - Guillaume Lample; Neil Zeghidour; Nicolas Usunier; Antoine Bordes; Ludovic Denoyer; Marc'Aurelio Ranzato (NIPS, 2017)

Gradient Episodic Memory for Continual Learning. - David Lopez-Paz; Marc'Aurelio Ranzato (NIPS, 2017)

Transformation-Based Models of Video Sequences. - Joost R. van Amersfoort; Anitha Kannan; Marc'Aurelio Ranzato; Arthur Szlam; Du Tran; Soumith Chintala (CoRR, 2017)

Gradient Episodic Memory for Continuum Learning. - David Lopez-Paz; Marc'Aurelio Ranzato (CoRR, 2017)

Training Language Models Using Target-Propagation. - Sam Wiseman; Sumit Chopra; Marc'Aurelio Ranzato; Arthur Szlam; Ruoyu Sun 004; Soumith Chintala; Nicolas Vasilache (CoRR, 2017)

Unsupervised Machine Translation Using Monolingual Corpora Only. - Guillaume Lample; Ludovic Denoyer; Marc'Aurelio Ranzato (CoRR, 2017)

Phrase-Based & Neural Unsupervised Machine Translation. - Guillaume Lample; Myle Ott; Alexis Conneau; Ludovic Denoyer; Marc'Aurelio Ranzato (EMNLP, 2018)

Unsupervised Machine Translation Using Monolingual Corpora Only. - Guillaume Lample; Alexis Conneau; Ludovic Denoyer; Marc'Aurelio Ranzato (ICLR (Poster), 2018)

Word translation without parallel data. - Guillaume Lample; Alexis Conneau; Marc'Aurelio Ranzato; Ludovic Denoyer; Hervé Jégou (ICLR (Poster), 2018)

Analyzing Uncertainty in Neural Machine Translation. - Myle Ott; Michael Auli; David Grangier; Marc'Aurelio Ranzato (ICML, 2018)

Classical Structured Prediction Losses for Sequence to Sequence Learning. - Sergey Edunov; Myle Ott; Michael Auli; David Grangier; Marc'Aurelio Ranzato (NAACL-HLT, 2018)

Lightweight Adaptive Mixture of Neural and N-gram Language Models. - Anton Bakhtin; Arthur Szlam; Marc'Aurelio Ranzato; Edouard Grave (CoRR, 2018)

Multiple-Attribute Text Style Transfer. - Sandeep Subramanian; Guillaume Lample; Eric Michael Smith; Ludovic Denoyer; Marc'Aurelio Ranzato; Y-Lan Boureau (CoRR, 2018)

Facebook AI's WAT19 Myanmar-English Translation Task Submission. - Peng-Jen Chen; Jiajun Shen; Matt Le 001; Vishrav Chaudhary; Ahmed El-Kishky; Guillaume Wenzek; Myle Ott; Marc'Aurelio Ranzato (WAT@EMNLP-IJCNLP, 2019)

The FLORES Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English. - Francisco Guzmán; Peng-Jen Chen; Myle Ott; Juan Miguel Pino; Guillaume Lample; Philipp Koehn; Vishrav Chaudhary; Marc'Aurelio Ranzato (EMNLP/IJCNLP (1), 2019)

Task-Driven Modular Networks for Zero-Shot Compositional Learning. - Senthil Purushwalkam; Maximilian Nickel; Abhinav Gupta 001; Marc'Aurelio Ranzato (ICCV, 2019)

Efficient Lifelong Learning with A-GEM. - Arslan Chaudhry; Marc'Aurelio Ranzato; Marcus Rohrbach; Mohamed Elhoseiny (ICLR (Poster), 2019)

Multiple-Attribute Text Rewriting. - Guillaume Lample; Sandeep Subramanian; Eric Michael Smith; Ludovic Denoyer; Marc'Aurelio Ranzato; Y-Lan Boureau (ICLR (Poster), 2019)

Mixture Models for Diverse Machine Translation: Tricks of the Trade. - Tianxiao Shen; Myle Ott; Michael Auli; Marc'Aurelio Ranzato (ICML, 2019)

Large Memory Layers with Product Keys. - Guillaume Lample; Alexandre Sablayrolles; Marc'Aurelio Ranzato; Ludovic Denoyer; Hervé Jégou (NeurIPS, 2019)

Two New Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English. - Francisco Guzmán; Peng-Jen Chen; Myle Ott; Juan Miguel Pino; Guillaume Lample; Philipp Koehn; Vishrav Chaudhary; Marc'Aurelio Ranzato (CoRR, 2019)

Continual Learning with Tiny Episodic Memories. - Arslan Chaudhry; Marcus Rohrbach; Mohamed Elhoseiny; Thalaiyasingam Ajanthan; Puneet Kumar Dokania; Philip H. S. Torr; Marc'Aurelio Ranzato (CoRR, 2019)

Real or Fake? Learning to Discriminate Machine from Human Generated Text. - Anton Bakhtin; Sam Gross; Myle Ott; Yuntian Deng; Marc'Aurelio Ranzato; Arthur Szlam (CoRR, 2019)

On The Evaluation of Machine Translation Systems Trained With Back-Translation. - Sergey Edunov; Myle Ott; Marc'Aurelio Ranzato; Michael Auli (CoRR, 2019)

On The Evaluation of Machine Translation SystemsTrained With Back-Translation. - Sergey Edunov; Myle Ott; Marc'Aurelio Ranzato; Michael Auli (ACL, 2020)

Residual Energy-Based Models for Text Generation. - Yuntian Deng; Anton Bakhtin; Myle Ott; Arthur Szlam; Marc'Aurelio Ranzato (ICLR, 2020)

Revisiting Self-Training for Neural Sequence Generation. - Junxian He; Jiatao Gu; Jiajun Shen; Marc'Aurelio Ranzato (ICLR, 2020)

Energy-Based Models for Text. - Anton Bakhtin; Yuntian Deng; Sam Gross; Myle Ott; Marc'Aurelio Ranzato; Arthur Szlam (CoRR, 2020)

Multi-scale Transformer Language Models. - Sandeep Subramanian; Ronan Collobert; Marc'Aurelio Ranzato; Y-Lan Boureau (CoRR, 2020)

Few-shot Sequence Learning with Transformers. - Lajanugen Logeswaran; Ann Lee 001; Myle Ott; Honglak Lee; Marc'Aurelio Ranzato; Arthur Szlam (CoRR, 2020)

Discriminative Reranking for Neural Machine Translation. - Ann Lee 001; Michael Auli; Marc'Aurelio Ranzato (ACL/IJCNLP (1), 2021)

The Source-Target Domain Mismatch Problem in Machine Translation. - Jiajun Shen; Peng-Jen Chen; Matt Le 001; Junxian He; Jiatao Gu; Myle Ott; Michael Auli; Marc'Aurelio Ranzato (EACL, 2021)

Efficient Continual Learning with Modular Networks and Task-Driven Priors. - Tom Veniat; Ludovic Denoyer; Marc'Aurelio Ranzato (ICLR, 2021)

Residual Energy-Based Models for Text. - Anton Bakhtin; Yuntian Deng; Sam Gross; Myle Ott; Marc'Aurelio Ranzato; Arthur Szlam (J. Mach. Learn. Res., 2021)

On Anytime Learning at Macroscale. - Lucas Caccia; Jing Xu; Myle Ott; Marc'Aurelio Ranzato; Ludovic Denoyer (CoLLAs, 2022)

Unified Scaling Laws for Routed Language Models. - Aidan Clark; Diego de Las Casas; Aurelia Guy; Arthur Mensch; Michela Paganini; Jordan Hoffmann; Bogdan Damoc; Blake A. Hechtman; Trevor Cai; Sebastian Borgeaud; George van den Driessche 002; Eliza Rutherford; et al. (ICML, 2022)

Towards Learning Universal Hyperparameter Optimizers with Transformers. - Yutian Chen 001; Xingyou Song; Chansoo Lee; Zi Wang; Richard Zhang 003; David Dohan; Kazuya Kawakami; Greg Kochanski; Arnaud Doucet; Marc'Aurelio Ranzato; Sagi Perel; Nando de Freitas (NeurIPS, 2022)

Multi-step Planning for Automated Hyperparameter Optimization with OptFormer. - Lucio M. Dery; Abram L. Friesen; Nando de Freitas; Marc'Aurelio Ranzato; Yutian Chen 001 (CoRR, 2022)

NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. - Jörg Bornschein; Alexandre Galashov; Ross Hemsley; Amal Rannen-Triki; Yutian Chen 001; Arslan Chaudhry; Xu Owen He; Arthur Douillard; Massimo Caccia; Qixuang Feng; Jiajun Shen; Sylvestre-Alvise Rebuffi; et al. (CoRR, 2022)

The Flores-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation. - Naman Goyal 001; Cynthia Gao; Vishrav Chaudhary; Peng-Jen Chen; Guillaume Wenzek; Da Ju; Sanjana Krishnan; Marc'Aurelio Ranzato; Francisco Guzmán; Angela Fan (Trans. Assoc. Comput. Linguistics, 2022)

Towards Compute-Optimal Transfer Learning. - Massimo Caccia; Alexandre Galashov; Arthur Douillard; Amal Rannen-Triki; Dushyant Rao; Michela Paganini; Laurent Charlin; Marc'Aurelio Ranzato; Razvan Pascanu (CoRR, 2023)

Towards Robust and Efficient Continual Language Learning. - Adam Fisch; Amal Rannen-Triki; Razvan Pascanu; Jörg Bornschein; Angeliki Lazaridou; Elena Gribovskaya; Marc'Aurelio Ranzato (CoRR, 2023)

DiLoCo: Distributed Low-Communication Training of Language Models. - Arthur Douillard; Qixuang Feng; Andrei A. Rusu; Rachita Chhaparia; Yani Donchev; Adhiguna Kuncoro; Marc'Aurelio Ranzato; Arthur Szlam; Jiajun Shen (CoRR, 2023)

Nevis'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. - Jörg Bornschein; Alexandre Galashov; Ross Hemsley; Amal Rannen-Triki; Yutian Chen 001; Arslan Chaudhry; Xu Owen He; Arthur Douillard; Massimo Caccia; Qixuan Feng; Jiajun Shen; Sylvestre-Alvise Rebuffi; et al. (J. Mach. Learn. Res., 2023)

Asynchronous Local-SGD Training for Language Modeling. - Bo Liu; Rachita Chhaparia; Arthur Douillard; Satyen Kale; Andrei A. Rusu; Jiajun Shen; Arthur Szlam; Marc'Aurelio Ranzato (CoRR, 2024)

DiPaCo: Distributed Path Composition. - Arthur Douillard; Qixuan Feng; Andrei A. Rusu; Adhiguna Kuncoro; Yani Donchev; Rachita Chhaparia; Ionel Gog; Marc'Aurelio Ranzato; Jiajun Shen; Arthur Szlam (CoRR, 2024)

Streaming DiLoCo with overlapping communication: Towards a Distributed Free Lunch. - Arthur Douillard; Yanislav Donchev; Keith Rush; Satyen Kale; Zachary Charles; Zachary Garrett; Gabriel Teston; Dave Lacey; Ross McIlroy; Jiajun Shen; Alexandre Ramé; Arthur Szlam; et al. (CoRR, 2025)