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Yashas Annadani
Yashas Annadani
KTH Stockholm
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
2112018
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
132021
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
92021
Structural autoencoders improve representations for generation and transfer
F Leeb, Y Annadani, S Bauer, B Schölkopf
8*2020
Growbit: Incremental hashing for cross-modal retrieval
D Mandal, Y Annadani, S Biswas
Asian Conference on Computer Vision, 305-321, 2018
82018
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
62018
Sliding dictionary based sparse representation for action recognition
Y Annadani, DL Rakshith, S Biswas
arXiv preprint arXiv:1611.00218, 2016
62016
Interventions, where and how? experimental design for causal models at scale
P Tigas, Y Annadani, A Jesson, B Schölkopf, Y Gal, S Bauer
arXiv preprint arXiv:2203.02016, 2022
22022
Latent Variable Models for Bayesian Causal Discovery
J Subramanian, Y Annadani, I Sheth, S Bauer, D Nowrouzezahrai, ...
arXiv preprint arXiv:2207.05723, 2022
2022
Interventions, Where and How? Bayesian Active Causal Discovery at Scale
P Tigas, Y Annadani, AJ OATML, YG OATML, SBKTH Stockholm
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Articles 1–10