Larochelle, Hugo

Domain-Adversarial Training of Neural Networks

Ganin, Y., Ustinova, E., Ajakan, H., Germain, P., Larochelle, H., Laviolette, F., Marchand, M., & Lempitsky, V. (2017) · Advances in Computer Vision and Pattern Recognition

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 8,318

Extracting and composing robust features with denoising autoencoders

Vincent, P., Larochelle, H., Bengio, Y., & Manzagol, P.-A. (2008) · Proceedings of the 25th international conference on Machine learning - ICML '08

Neural Networks and ApplicationsFace and Expression Recognition

Cited by 7,436

Practical Bayesian Optimization of Machine Learning Algorithms

Snoek, J., Larochelle, H., & Adams, R. P. (2012) · arXiv

Advanced Bandit Algorithms ResearchMachine Learning and Data Classification

Cited by 6,691

Greedy layer-wise training of deep networks

Bengio, Y., Lamblin, P., Popovici, D., & Larochelle, H. (2007) · Advances in Neural Information Processing Systems 19

Neural Networks and ApplicationsStochastic Gradient Optimization Techniques

Cited by 4,841

Deep learning with coherent nanophotonic circuits

Shen, Y., Harris, N. C., Skirlo, S., Prabhu, M., Baehr-Jones, T., Hochberg, M., Sun, X., Zhao, S., Larochelle, H., Englund, D., et al. (2017) · Nature Photonics

Neural Networks and Reservoir ComputingPhotonic and Optical Devices

Cited by 3,340

Brain tumor segmentation with Deep Neural Networks

Havaei, M., Davy, A., Warde-Farley, D., Biard, A., Courville, A., Bengio, Y., Pal, C., Jodoin, P.-M., & Larochelle, H. (2017) · Medical Image Analysis

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 3,278

Brain Tumor Segmentation with Deep Neural Networks

Havaei, M., Davy, A., Warde-Farley, D., Biard, A., Courville, A., Bengio, Y., Pal, C., Jodoin, P.-M., & Larochelle, H. (2015) · arXiv

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 3,278

Machine behaviour

Rahwan, I., Cebrian, M., Obradovich, N., Bongard, J., Bonnefon, J.-F., Breazeal, C., Crandall, J. W., Christakis, N. A., Couzin, I. D., Jackson, M. O., et al. (2019) · Nature

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 1,364

Describing Videos by Exploiting Temporal Structure

Yao, L., Torabi, A., Cho, K., Ballas, N., Pal, C., Larochelle, H., & Courville, A. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV)

Multimodal Machine Learning ApplicationsHuman Pose and Action Recognition

Cited by 1,035

Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program)

Pineau, J., Vincent-Lamarre, P., Sinha, K., Larivière, V., Beygelzimer, A., d'Alché-Buc, F., Fox, E., & Larochelle, H. (2020) · arXiv

Scientific Computing and Data ManagementAcademic Publishing and Open Access

Cited by 232

A Deep and Tractable Density Estimator

Uria, B., Murray, I., & Larochelle, H. (2013) · arXiv

Neural Networks and ApplicationsGaussian Processes and Bayesian Inference

Cited by 100

Language GANs Falling Short

Caccia, M., Caccia, L., Fedus, W., Larochelle, H., Pineau, J., & Charlin, L. (2018) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 83

Small-GAN: Speeding Up GAN Training Using Core-sets

Sinha, S., Zhang, H., Goyal, A., Bengio, Y., Larochelle, H., & Odena, A. (2019) · arXiv

Generative Adversarial Networks and Image SynthesisStochastic Gradient Optimization Techniques

Cited by 56

Many-Shot In-Context Learning

Agarwal, R., Singh, A., Zhang, L. M., Bohnet, B., Rosias, L., Chan, S., Zhang, B., Anand, A., Abbas, Z., Nova, A., et al. (2024) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 35

Repository-Level Prompt Generation for Large Language Models of Code

Shrivastava, D., Larochelle, H., & Tarlow, D. (2022) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 27