Lamblin, Pascal

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

Theano: new features and speed improvements

Bastien, F., Lamblin, P., Pascanu, R., Bergstra, J., Goodfellow, I., Bergeron, A., Bouchard, N., Warde-Farley, D., & Bengio, Y. (2012) · arXiv

Parallel Computing and Optimization TechniquesNeural Networks and Applications

Cited by 1,005

Combining modality specific deep neural networks for emotion recognition in video

Kahou, S. E., Pal, C., Bouthillier, X., Froumenty, P., Gülçehre, Ç., Memisevic, R., Vincent, P., Courville, A., Bengio, Y., Ferrari, R. C., et al. (2013) · Proceedings of the 15th ACM on International conference on multimodal interaction

Emotion and Mood RecognitionFace recognition and analysis

Cited by 391

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69

Resolving Code Review Comments with Machine Learning

Froemmgen, A., Austin, J., Choy, P., Ghelani, N., Kharatyan, L., Surita, G., Khrapko, E., Lamblin, P., Manzagol, P.-A., Revaj, M., et al. (2024) · Proceedings of the 46th International Conference on Software Engineering: Software Engineering in Practice

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 21