Marc’aurelio Ranzato
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Marc’aurelio Ranzato's AcademicInfluence.com Rankings
Marc’aurelio Ranzatocomputer-science Degrees
Computer Science
#9272
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#9739
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Algorithms
#374
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#379
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Machine Learning
#4013
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#4061
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Artificial Intelligence
#4349
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#4409
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Computer Science
Marc’aurelio Ranzato's Degrees
- PhD Computer Science New York University
- Masters Computer Science University of Trento
- Bachelors Computer Science University of Trento
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Why Is Marc’aurelio Ranzato Influential?
(Suggest an Edit or Addition)Marc’aurelio Ranzato's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- DeepFace: Closing the Gap to Human-Level Performance in Face Verification (2014) (5587)
- Large Scale Distributed Deep Networks (2012) (3316)
- DeViSE: A Deep Visual-Semantic Embedding Model (2013) (2243)
- What is the best multi-stage architecture for object recognition? (2009) (2242)
- Building high-level features using large scale unsupervised learning (2011) (2207)
- Gradient Episodic Memory for Continual Learning (2017) (1482)
- Sequence Level Training with Recurrent Neural Networks (2015) (1373)
- Word Translation Without Parallel Data (2017) (1315)
- Efficient Learning of Sparse Representations with an Energy-Based Model (2006) (1289)
- Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition (2007) (1163)
- Predicting Parameters in Deep Learning (2013) (1153)
- Unsupervised Machine Translation Using Monolingual Corpora Only (2017) (921)
- Sparse Feature Learning for Deep Belief Networks (2007) (876)
- Efficient Lifelong Learning with A-GEM (2018) (767)
- Phrase-Based & Neural Unsupervised Machine Translation (2018) (601)
- On rectified linear units for speech processing (2013) (516)
- Fader Networks: Manipulating Images by Sliding Attributes (2017) (494)
- PANDA: Pose Aligned Networks for Deep Attribute Modeling (2013) (490)
- Video (language) modeling: a baseline for generative models of natural videos (2014) (419)
- Learning invariant features through topographic filter maps (2009) (353)
- Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine (2010) (331)
- Multilingual acoustic models using distributed deep neural networks (2013) (314)
- On Tiny Episodic Memories in Continual Learning (2019) (267)
- Modeling pixel means and covariances using factorized third-order boltzmann machines (2010) (263)
- Web-scale training for face identification (2014) (254)
- Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition (2010) (252)
- Learning Longer Memory in Recurrent Neural Networks (2014) (246)
- Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images (2010) (245)
- Semi-supervised learning of compact document representations with deep networks (2008) (234)
- On deep generative models with applications to recognition (2011) (221)
- The FLORES Evaluation Datasets for Low-Resource Machine Translation: Nepali–English and Sinhala–English (2019) (215)
- Analyzing Uncertainty in Neural Machine Translation (2018) (197)
- Learning Factored Representations in a Deep Mixture of Experts (2013) (194)
- Continual Learning with Tiny Episodic Memories (2019) (192)
- Revisiting Self-Training for Neural Sequence Generation (2019) (189)
- Multiple-Attribute Text Rewriting (2018) (173)
- An empirical study of learning rates in deep neural networks for speech recognition (2013) (166)
- Classical Structured Prediction Losses for Sequence to Sequence Learning (2017) (160)
- The Flores-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation (2021) (155)
- Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie Reviews (2014) (139)
- Automatic recognition of biological particles in microscopic images (2007) (120)
- A Unified Energy-Based Framework for Unsupervised Learning (2007) (118)
- Task-Driven Modular Networks for Zero-Shot Compositional Learning (2019) (105)
- Dialogue Learning With Human-In-The-Loop (2016) (103)
- Mixture Models for Diverse Machine Translation: Tricks of the Trade (2019) (98)
- Multi-GPU Training of ConvNets (2013) (97)
- Large Memory Layers with Product Keys (2019) (92)
- On Autoencoders and Score Matching for Energy Based Models (2011) (91)
- Learning through Dialogue Interactions by Asking Questions (2016) (82)
- Generating more realistic images using gated MRF's (2010) (80)
- On The Evaluation of Machine Translation SystemsTrained With Back-Translation (2019) (75)
- Transformation-Based Models of Video Sequences (2017) (67)
- Multiple-Attribute Text Style Transfer (2018) (63)
- Hard Mixtures of Experts for Large Scale Weakly Supervised Vision (2017) (62)
- Modeling Natural Images Using Gated MRFs (2013) (58)
- Real or Fake? Learning to Discriminate Machine from Human Generated Text (2019) (55)
- Efficient Continual Learning with Modular Networks and Task-Driven Priors (2020) (50)
- Energy-Based Models in Document Recognition and Computer Vision (2007) (47)
- Dynamic auto-encoders for semantic indexing (2010) (35)
- Guest Editorial: Deep Learning (2015) (26)
- Facebook AI’s WAT19 Myanmar-English Translation Task Submission (2019) (26)
- A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images (2007) (26)
- Unsupervised Learning of Feature Hierarchies (2009) (20)
- The Source-Target Domain Mismatch Problem in Machine Translation (2019) (19)
- Scale-invariant learning and convolutional networks (2015) (19)
- Discriminative Reranking for Neural Machine Translation (2021) (17)
- On Learning Where To Look (2014) (16)
- Learning Through Dialogue Interactions (2016) (15)
- Residual Energy-Based Models for Text (2021) (15)
- E cient Learning of Sparse Overcomplete Representations with an Energy-Based Model (2006) (15)
- On Anytime Learning at Macroscale (2021) (13)
- Towards Learning Universal Hyperparameter Optimizers with Transformers (2022) (12)
- Unsupervised image ranking (2009) (12)
- Convolutional networks and learning invariant to homogeneous multiplicative scalings (2015) (11)
- Few-shot Sequence Learning with Transformers (2020) (9)
- Energy-Based Models for Text (2020) (9)
- Learning in Informal Settings (2012) (8)
- Multi-scale Transformer Language Models (2020) (8)
- Training Language Models Using Target-Propagation (2017) (8)
- Lightweight Adaptive Mixture of Neural and N-gram Language Models (2018) (8)
- Fader Networks: Generating Image Variations by Sliding Attribute Values (2017) (5)
- Learning and Development After School (2012) (5)
- How to generate realistic images using gated MRF ’ s (2010) (5)
- Single Server Multi-GPU Training of ConvNets (2013) (4)
- NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research (2022) (2)
- Learning Through the Breach: Language Socialization (2012) (2)
- On-Line Learning of Long-Range Obstacle Detection for Off-Road Robots (2006) (2)
- Learning from Text (2012) (2)
- Diverse Machine Translation with a Single Multinomial Latent Variable (2018) (1)
- High-Accuracy Object Recognition with a New Convolutional Net Architecture and Learning Algorithm (2009) (1)
- UvA-DARE (Digital Academic Repository) SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks (2020) (1)
- GenEval: A Benchmark Suite for Evaluating Generative Models (2018) (0)
- Learning Goals: (2020) (0)
- Towards Compute-Optimal Transfer Learning (2023) (0)
- Web-Scale Transfer Learning for Unconstrained 1 : N Face Identification (2015) (0)
- Guest Editorial: Deep Learning (2015) (0)
- UMAN-IN-THEL OOP (2017) (0)
- Residual EBMs: Does Real vs. Fake Text Discrimination Generalize? (2019) (0)
- Recurrent Neural Networks (2015) (0)
- Multi-step Planning for Automated Hyperparameter Optimization with OptFormer (2022) (0)
- Under Review as a Conference Paper at Iclr 2017 Learning through Dialogue Interactions (2016) (0)
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