@anish144.bsky.social
PhD researcher in Machine Learning at Imperial College. Visiting at University of Oxford.
Interested in all things involving causality and Bayesian machine learning. Recently I have also been interested in scaling theory.
https://anish144.github.io/
Interested in all things involving causality and Bayesian machine learning. Recently I have also been interested in scaling theory.
https://anish144.github.io/
📢New #ICML2025 paper: "Continuous Bayesian Model Selection for Multivariate Causal Discovery".
We propose a Bayesian causal model that allows for scalable causal discovery without restrictive model assumptions.
Paper: arxiv.org/abs/2411.10154
Code: github.com/Anish144/Con...
🧵1/14
We propose a Bayesian causal model that allows for scalable causal discovery without restrictive model assumptions.
Paper: arxiv.org/abs/2411.10154
Code: github.com/Anish144/Con...
🧵1/14
July 10, 2025 at 6:07 PM
📢New #ICML2025 paper: "Continuous Bayesian Model Selection for Multivariate Causal Discovery".
We propose a Bayesian causal model that allows for scalable causal discovery without restrictive model assumptions.
Paper: arxiv.org/abs/2411.10154
Code: github.com/Anish144/Con...
🧵1/14
We propose a Bayesian causal model that allows for scalable causal discovery without restrictive model assumptions.
Paper: arxiv.org/abs/2411.10154
Code: github.com/Anish144/Con...
🧵1/14
Understanding causes is key to science. Finite observational data alone isn't enough. While Bayes offers a framework to deal with this, the calculations are often intractable. We introduce a method to accurately approximate the posterior over causal structures.
#ICLR2025 🧵1/15
#ICLR2025 🧵1/15
April 19, 2025 at 5:39 PM
Understanding causes is key to science. Finite observational data alone isn't enough. While Bayes offers a framework to deal with this, the calculations are often intractable. We introduce a method to accurately approximate the posterior over causal structures.
#ICLR2025 🧵1/15
#ICLR2025 🧵1/15
Reposted
I wrote a little blog post for the Neptune.ai blog about our ICML position paper on Bayesian Deep Learning: neptune.ai/blog/bayesia...
Bayesian Deep Learning is Needed in the Age of Large-Scale AI [Paper Reflection]
In particular, we point out that there are many other metrics beyond accuracy, such as uncertainty calibration, which we have to take into account to ensure that better models also translate to better...
neptune.ai
March 13, 2025 at 5:53 PM
I wrote a little blog post for the Neptune.ai blog about our ICML position paper on Bayesian Deep Learning: neptune.ai/blog/bayesia...
Reposted
Looking forward to reading this!
"The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications"
arxiv.org/abs/2412.01953
#stats #mlsky #blueskai 📈📉
"The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications"
arxiv.org/abs/2412.01953
#stats #mlsky #blueskai 📈📉
December 4, 2024 at 3:50 AM
Looking forward to reading this!
"The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications"
arxiv.org/abs/2412.01953
#stats #mlsky #blueskai 📈📉
"The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications"
arxiv.org/abs/2412.01953
#stats #mlsky #blueskai 📈📉