Desi R. Ivanova

19 papers A* 6A 1Journal 11Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Extending Epistemic Uncertainty Beyond Parameters Would Assist in Designing Reliable LLMs. CoRR T. Duy Nguyen-Hien, Desi R. Ivanova, Yee Whye Teh, Wee Sun Lee
2025	A	`conf`	Is Merging Worth It? Securely Evaluating the Information Gain for Causal Dataset Acquisition. AISTATS Jake Fawkes, Lucile Ter-Minassian, Desi R. Ivanova, Uri Shalit, Christopher C. Holmes
2025	J	`jnl`	JADAI: Jointly Amortizing Adaptive Design and Bayesian Inference. CoRR Niels Bracher, Lars Kühmichel, Desi R. Ivanova, Xavier Intes, Paul-Christian Bürkner, Stefan T. Radev
2025	—	`conf`	Position: Don't Use the CLT in LLM Evals With Fewer Than a Few Hundred Datapoints. ICML (Position Papers) Sam Bowyer, Laurence Aitchison, Desi R. Ivanova
2025	J	`jnl`	Position: Don't use the CLT in LLM evals with fewer than a few hundred datapoints. CoRR Sam Bowyer, Laurence Aitchison, Desi R. Ivanova
2025	A*	`conf`	Step-DAD: Semi-Amortized Policy-Based Bayesian Experimental Design. ICML Marcel Hedman, Desi R. Ivanova, Cong Guan, Tom Rainforth
2025	J	`jnl`	Step-DAD: Semi-Amortized Policy-Based Bayesian Experimental Design. CoRR Marcel Hedman, Desi R. Ivanova, Cong Guan, Tom Rainforth
2024	J	`jnl`	Is merging worth it? Securely evaluating the information gain for causal dataset acquisition. CoRR Jake Fawkes, Lucile Ter-Minassian, Desi R. Ivanova, Uri Shalit, Christopher C. Holmes
2024	A*	`conf`	Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference. ICML Marvin Schmitt, Desi R. Ivanova, Daniel Habermann, Ullrich Köthe, Paul-Christian Bürkner, Stefan T. Radev
2023	A*	`conf`	CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design. ICML Desi R. Ivanova, Joel Jennings, Tom Rainforth, Cheng Zhang, Adam Foster
2023	J	`jnl`	CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design. CoRR Desi R. Ivanova, Joel Jennings, Tom Rainforth, Cheng Zhang, Adam Foster
2023	A*	`conf`	Differentiable Multi-Target Causal Bayesian Experimental Design. ICML Panagiotis Tigas, Yashas Annadani, Desi R. Ivanova, Andrew Jesson, Yarin Gal, Adam Foster, Stefan Bauer
2023	J	`jnl`	Differentiable Multi-Target Causal Bayesian Experimental Design. CoRR Yashas Annadani, Panagiotis Tigas, Desi R. Ivanova, Andrew Jesson, Yarin Gal, Adam Foster, Stefan Bauer
2023	J	`jnl`	Modern Bayesian Experimental Design. CoRR Tom Rainforth, Adam Foster, Desi R. Ivanova, Freddie Bickford Smith
2022	J	`jnl`	Efficient Real-world Testing of Causal Decision Making via Bayesian Experimental Design for Contextual Optimisation. CoRR Desi R. Ivanova, Joel Jennings, Cheng Zhang, Adam Foster
2021	A*	`conf`	Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design. ICML Adam Foster, Desi R. Ivanova, Ilyas Malik, Tom Rainforth
2021	J	`jnl`	Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design. CoRR Adam Foster, Desi R. Ivanova, Ilyas Malik, Tom Rainforth
2021	A*	`conf`	Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods. NeurIPS Desi R. Ivanova, Adam Foster, Steven Kleinegesse, Michael U. Gutmann, Thomas Rainforth
2021	J	`jnl`	Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods. CoRR Desi R. Ivanova, Adam Foster, Steven Kleinegesse, Michael U. Gutmann, Tom Rainforth