Ayush Bharti
@ayushbharti.bsky.social
Academy Research Fellow at the Dept. of Computer Science, Aalto University, Finland. Affiliated with the Finnish Center for Artificial Intelligence.
Website: http://bharti-ayush.github.io
Website: http://bharti-ayush.github.io
Thank you so much! Glad you liked it.
May 2, 2025 at 3:24 PM
Thank you so much! Glad you liked it.
Doing so saves hours of computation time for the radio propagation model without any degradation in performance. (5/5)
May 2, 2025 at 6:45 AM
Doing so saves hours of computation time for the radio propagation model without any degradation in performance. (5/5)
Sampling from the cost-aware proposal is done via rejection sampling, and self-normalised importance weights are used to target the SBI posterior. (4/5)
May 2, 2025 at 6:45 AM
Sampling from the cost-aware proposal is done via rejection sampling, and self-normalised importance weights are used to target the SBI posterior. (4/5)
We propose to sample from a cost-aware proposal to encourage sampling from the cheaper parameterisations of the model. (3/5)
May 2, 2025 at 6:45 AM
We propose to sample from a cost-aware proposal to encourage sampling from the cheaper parameterisations of the model. (3/5)
Oftentimes, this computational cost varies with the parameter value, as is the case with this model from wireless communications field where the cost increases linearly. (2/5)
May 2, 2025 at 6:45 AM
Oftentimes, this computational cost varies with the parameter value, as is the case with this model from wireless communications field where the cost increases linearly. (2/5)
Thread below:
Popular SBI methods such as Approximate Bayesian computation (ABC), neural posterior estimation (NPE) and neural likelihood estimation (NLE) require running the simulator thousands of times, which can be a computational bottleneck. (1/5)
Popular SBI methods such as Approximate Bayesian computation (ABC), neural posterior estimation (NPE) and neural likelihood estimation (NLE) require running the simulator thousands of times, which can be a computational bottleneck. (1/5)
May 2, 2025 at 6:45 AM
Thread below:
Popular SBI methods such as Approximate Bayesian computation (ABC), neural posterior estimation (NPE) and neural likelihood estimation (NLE) require running the simulator thousands of times, which can be a computational bottleneck. (1/5)
Popular SBI methods such as Approximate Bayesian computation (ABC), neural posterior estimation (NPE) and neural likelihood estimation (NLE) require running the simulator thousands of times, which can be a computational bottleneck. (1/5)
Congratulations Matias!
December 10, 2024 at 2:17 PM
Congratulations Matias!
Looks very interesting. This goes to the top of my reading list 😀
November 21, 2024 at 6:25 AM
Looks very interesting. This goes to the top of my reading list 😀
Hi, I'd like to join if that's ok.
November 19, 2024 at 9:16 AM
Hi, I'd like to join if that's ok.