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Yashas Annadani
Yashas Annadani
Helmholtz AI, TU Munich
Verified email at ethz.ch - Homepage
Title
Cited by
Cited by
Year
Preserving semantic relations for zero-shot learning
Y Annadani, S Biswas
Proceedings of the IEEE conference on computer vision and pattern …, 2018
2532018
Learning neural causal models with active interventions
N Scherrer, O Bilaniuk, Y Annadani, A Goyal, P Schwab, B Schölkopf, ...
arXiv preprint arXiv:2109.02429, 2021
302021
Variational causal networks: Approximate bayesian inference over causal structures
Y Annadani, J Rothfuss, A Lacoste, N Scherrer, A Goyal, Y Bengio, ...
arXiv preprint arXiv:2106.07635, 2021
232021
Structure by Architecture: Structured Representations without Regularization
F Leeb, G Lanzillotta, Y Annadani, M Besserve, S Bauer, B Schölkopf
International Conference on Learning Representations, 2023
16*2023
Interventions, where and how? experimental design for causal models at scale
P Tigas, Y Annadani, A Jesson, B Schölkopf, Y Gal, S Bauer
Advances in Neural Information Processing Systems, 2022
152022
Growbit: Incremental hashing for cross-modal retrieval
D Mandal, Y Annadani, S Biswas
Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth …, 2019
92019
Augment and adapt: A simple approach to image tampering detection
Y Annadani, CV Jawahar
2018 24th International Conference on Pattern Recognition (ICPR), 2983-2988, 2018
72018
Sliding dictionary based sparse representation for action recognition
Y Annadani, DL Rakshith, S Biswas
arXiv preprint arXiv:1611.00218, 2016
72016
Trust Your : Gradient-based Intervention Targeting for Causal Discovery
M Olko, M Zając, A Nowak, N Scherrer, Y Annadani, S Bauer, Ł Kuciński, ...
arXiv preprint arXiv:2211.13715, 2022
22022
Differentiable Multi-Target Causal Bayesian Experimental Design
Y Annadani, P Tigas, DR Ivanova, A Jesson, Y Gal, A Foster, S Bauer
arXiv preprint arXiv:2302.10607, 2023
12023
Learning Latent Structural Causal Models
J Subramanian, Y Annadani, I Sheth, NR Ke, T Deleu, S Bauer, ...
arXiv preprint arXiv:2210.13583, 2022
12022
BayesDAG: Gradient-Based Posterior Sampling for Causal Discovery
Y Annadani, N Pawlowski, J Jennings, S Bauer, C Zhang, W Gong
arXiv preprint arXiv:2307.13917, 2023
2023
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