3 citations · 3 across the 3 of their papers we have counts for
6 papers
Amortized Inference of Causal Models via Conditional Fixed-Point Iterations
Divyat Mahajan, Jannes Gladrow, Agrin Hilmkil +2
Structural Causal Models (SCMs) offer a principled framework to reason about interventions and support out-of-distribution generalization, which are key goals in scientific discove…
Uncertainty-Guided Likelihood Tree Search
Julia Grosse, Ruotian Wu, Ahmad Rashid +4
Tree search is a fundamental tool for planning, as many sequential decision-making problems can be framed as searching over tree-structured spaces. We propose an uncertainty-guided…
A Fixed-Point Approach for Causal Generative Modeling
Meyer Scetbon, Joel Jennings, Agrin Hilmkil +2
We propose a novel formalism for describing Structural Causal Models (SCMs) as fixed-point problems on causally ordered variables, eliminating the need for Directed Acyclic Graphs…
Inverse Design of Photonic Crystal Surface Emitting Lasers is a Sequence Modeling Problem
Ceyao Zhang, Renjie Li, Cheng Zhang +2
Photonic Crystal Surface Emitting Lasers (PCSEL)'s inverse design demands expert knowledge in physics, materials science, and quantum mechanics which is prohibitively labor-intensi…
The Essential Role of Causality in Foundation World Models for Embodied AI
Tarun Gupta, Wenbo Gong, Chao Ma +11
Recent advances in foundation models, especially in large multi-modal models and conversational agents, have ignited interest in the potential of generally capable embodied agents.…
Learned Causal Method Prediction
Shantanu Gupta, Cheng Zhang, Agrin Hilmkil
For a given causal question, it is important to efficiently decide which causal inference method to use for a given dataset. This is challenging because causal methods typically re…