no code implementations • 6 Feb 2024 • Netta Ollikka, Amro Abbas, Andrea Perin, Markku Kilpeläinen, Stéphane Deny
Deep learning is closing the gap with humans on several object recognition benchmarks.
1 code implementation • 5 Feb 2024 • Bernard Spiegl, Andrea Perin, Stéphane Deny, Alexander Ilin
Deep learning is providing a wealth of new approaches to the old problem of novel view synthesis, from Neural Radiance Field (NeRF) based approaches to end-to-end style architectures.
no code implementations • 27 May 2023 • Omkar Ranadive, Nikhil Thakurdesai, Ari S Morcos, Matthew Leavitt, Stéphane Deny
Finally, in causal experiments where we regularize against class selectivity at different points in training, we show that the presence of class-selective neurons early in training is critical to the successful training of the network; in contrast, class-selective neurons can be suppressed later in training with little effect on final accuracy.
1 code implementation • 3 Feb 2023 • Shoaib Ahmed Siddiqui, David Krueger, Yann Lecun, Stéphane Deny
Current state-of-the-art deep networks are all powered by backpropagation.
1 code implementation • 16 Jul 2022 • Amro Abbas, Stéphane Deny
We show that classifying these images is still a challenge for all networks tested, with an average accuracy drop of 29. 5% compared to when the objects are presented upright.
24 code implementations • 4 Mar 2021 • Jure Zbontar, Li Jing, Ishan Misra, Yann Lecun, Stéphane Deny
This causes the embedding vectors of distorted versions of a sample to be similar, while minimizing the redundancy between the components of these vectors.
Ranked #11 on Image Classification on Places205
1 code implementation • 10 Feb 2021 • Diane Bouchacourt, Mark Ibrahim, Stéphane Deny
A core challenge in Machine Learning is to learn to disentangle natural factors of variation in data (e. g. object shape vs. pose).