Yashas Annadani

According to our database, Yashas Annadani authored at least 16 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

BayesDAG: Gradient-Based Posterior Sampling for Causal Discovery.

Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong

CoRR, 2023

Trust Your 𝛁: Gradient-based Intervention Targeting for Causal Discovery.

Mateusz Olko, Michal Zajac, Aleksandra Nowak, Nino Scherrer, Yashas Annadani, Stefan Bauer, Lukasz Kucinski, Piotr Milos

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

BayesDAG: Gradient-Based Posterior Inference for Causal Discovery.

Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Differentiable Multi-Target Causal Bayesian Experimental Design.

Panagiotis Tigas, Yashas Annadani, Desi R. Ivanova, Andrew Jesson, Yarin Gal, Adam Foster, Stefan Bauer

Proceedings of the International Conference on Machine Learning, 2023

Structure by Architecture: Structured Representations without Regularization.

Felix Leeb, Giulia Lanzillotta, Yashas Annadani, Michel Besserve, Stefan Bauer, Bernhard Schölkopf

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Learning Latent Structural Causal Models.

Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth, Nan Rosemary Ke, Tristan Deleu, Stefan Bauer, Derek Nowrouzezahrai, Samira Ebrahimi Kahou

CoRR, 2022

Latent Variable Models for Bayesian Causal Discovery.

Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth, Stefan Bauer, Derek Nowrouzezahrai, Samira Ebrahimi Kahou

CoRR, 2022

Interventions, Where and How? Experimental Design for Causal Models at Scale.

Panagiotis Tigas, Yashas Annadani, Andrew Jesson, Bernhard Schölkopf, Yarin Gal, Stefan Bauer

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Learning Neural Causal Models with Active Interventions.

Nino Scherrer, Olexa Bilaniuk, Yashas Annadani, Anirudh Goyal, Patrick Schwab, Bernhard Schölkopf, Michael C. Mozer, Yoshua Bengio, Stefan Bauer, Nan Rosemary Ke

CoRR, 2021

Variational Causal Networks: Approximate Bayesian Inference over Causal Structures.

Yashas Annadani, Jonas Rothfuss, Alexandre Lacoste, Nino Scherrer, Anirudh Goyal, Yoshua Bengio, Stefan Bauer

CoRR, 2021

2020

Structural Autoencoders Improve Representations for Generation and Transfer.

Felix Leeb, Yashas Annadani, Stefan Bauer, Bernhard Schölkopf

CoRR, 2020

2018

Augment and Adapt: A Simple Approach to Image Tampering Detection.

Yashas Annadani, C. V. Jawahar

Proceedings of the 24th International Conference on Pattern Recognition, 2018

Preserving Semantic Relations for Zero-Shot Learning.

Yashas Annadani, Soma Biswas

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

GrowBit: Incremental Hashing for Cross-Modal Retrieval.

Devraj Mandal, Yashas Annadani, Soma Biswas

Proceedings of the Computer Vision - ACCV 2018, 2018

2016

Sliding Dictionary Based Sparse Representation For Action Recognition.

Yashas Annadani, D. L. Rakshith, Soma Biswas

CoRR, 2016

Selfie Detection by Synergy-Constraint Based Convolutional Neural Network.

Yashas Annadani, Vijayakrishna Naganoor, Akshay Kumar Jagadish, Krishnan Chemmangat

Proceedings of the 12th International Conference on Signal-Image Technology & Internet-Based Systems, 2016