Hugo Larochelle
- Artificial Intelligence top 0.02%
- Computer Vision and Pattern Recognition top 0.05%
- Electrical and Electronic Engineering top 1%
- Signal Processing top 0.2%
- Radiology, Nuclear Medicine and Imaging top 0.5%
- Co-authors
- Yoshua BengioPascal VincentPierre-Antoine ManzagolIain MurraySachin RaviAaron CourvilleKarol GregorPierre‐Marc Jodoin
- Topics
- Generative Adversarial Networks and Image Synthesis (17 papers)Domain Adaptation and Few-Shot Learning (16 papers)Multimodal Machine Learning Applications (9 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceNature PhotonicsInternational Journal of Computer Vision
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Hugo Larochelle
75 papers receiving 19.6k citations
Hit Papers
Peers
Comparison fields: 5 of 205
- Artificial Intelligence 10.6k
- Computer Vision and Pattern Recognition 8.7k
- Electrical and Electronic Engineering 2.9k
- Signal Processing 1.9k
- Radiology, Nuclear Medicine and Imaging 1.5k
Countries citing papers authored by Hugo Larochelle
This map shows the geographic impact of Hugo Larochelle's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hugo Larochelle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hugo Larochelle more than expected).
Fields of papers citing papers by Hugo Larochelle
This network shows the impact of papers produced by Hugo Larochelle. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hugo Larochelle. The network helps show where Hugo Larochelle may publish in the future.
Co-authorship network of co-authors of Hugo Larochelle
This figure shows the co-authorship network connecting the top 25 collaborators of Hugo Larochelle. A scholar is included among the top collaborators of Hugo Larochelle based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hugo Larochelle. Hugo Larochelle is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | A Universal Representation Transformer Layer for Few-Shot Image Classification | 7 |
| 3 | A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches | 2 |
| 4 | Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling | 3 |
| 5 | InfoBot: Transfer and Exploration via the Information Bottleneck | 8 |
| 6 | Meta-Learning for Semi-Supervised Few-Shot Classification | 73 |
| 7 | Meta-Learning for Batch Mode Active Learning. | 12 |
| 8 | Optimization as a Model for Few-Shot Learningbreakdown → | 1109 |
| 9 | Recurrent Mixture Density Network for Spatiotemporal Visual Attention | 15 |
| 10 | Brain tumor segmentation with Deep Neural Networksbreakdown → | 2102 |
| 11 | Describing Videos by Exploiting Temporal Structurebreakdown → | 593 |
| 12 | Sequential model-based ensemble optimization | 2 |
| 13 | A Neural Autoregressive Topic Model | 110 |
| 14 | Learning attentional policies for tracking and recognition in video with deep networks | 26 |
| 15 | The Neural Autoregressive Distribution Estimator | 166 |
| 16 | Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterionbreakdown → | 3317 |
| 17 | Deep Learning using Robust Interdependent Codes | 17 |
| 18 | Exploring Strategies for Training Deep Neural Networksbreakdown → | 758 |
| 19 | Distributed Representation Prediction for Generalization to New Words | 1 |
| 20 | Non-Local Manifold Parzen Windows | 31 |
About Hugo Larochelle
Hugo Larochelle is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 77 papers that have together received 20.6k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (17 papers), Domain Adaptation and Few-Shot Learning (16 papers) and Multimodal Machine Learning Applications (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (8.7k citations), Artificial Intelligence (10.6k citations) and Neurology (1.5k citations). Hugo Larochelle has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Yoshua Bengio, Pascal Vincent, Pierre-Antoine Manzagol, Iain Murray, Sachin Ravi, Aaron Courville, Karol Gregor, Pierre‐Marc Jodoin, Mohammad Havaei and David Warde-Farley. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Nature Photonics and International Journal of Computer Vision.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.