Adam Golinski - RankMe

24 papers A* 5A 1Journal 16Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	BED-LLM: Intelligent Information Gathering with LLMs and Bayesian Experimental Design. CoRR Deepro Choudhury, Sinead Williamson, Adam Golinski, Ning Miao, Freddie Bickford Smith, Michael Kirchhof, Yizhe Zhang, Tom Rainforth
2025	A*	`conf`	Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs. ICML Yinong Oliver Wang, Nivedha Sivakumar, Falaah Arif Khan, Katherine Metcalf, Adam Golinski, Natalie Mackraz, Barry-John Theobald, Luca Zappella, Nicholas Apostoloff
2025	J	`jnl`	Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs. CoRR Yinong Oliver Wang, Nivedha Sivakumar, Falaah Arif Khan, Rin Metcalf Susa, Adam Golinski, Natalie Mackraz, Barry-John Theobald, Luca Zappella, Nicholas Apostoloff
2025	—	`conf`	Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias Results. ACL (2) Andrea Santilli, Adam Golinski, Michael Kirchhof, Federico Danieli, Arno Blaas, Miao Xiong, Luca Zappella, Sinead Williamson
2025	J	`jnl`	Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias Results. CoRR Andrea Santilli, Adam Golinski, Michael Kirchhof, Federico Danieli, Arno Blaas, Miao Xiong, Luca Zappella, Sinead Williamson
2025	J	`jnl`	Self-reflective Uncertainties: Do LLMs Know Their Internal Answer Distribution? CoRR Michael Kirchhof, Luca Füger, Adam Golinski, Eeshan Gunesh Dhekane, Arno Blaas, Sinead Williamson
2025	J	`jnl`	Trained on Tokens, Calibrated on Concepts: The Emergence of Semantic Calibration in LLMs. CoRR Preetum Nakkiran, Arwen Bradley, Adam Golinski, Eugène Ndiaye, Michael Kirchhof, Sinead Williamson
2024	J	`jnl`	Considerations for Distribution Shift Robustness of Diagnostic Models in Healthcare. CoRR Arno Blaas, Adam Golinski, Andrew C. Miller, Luca Zappella, Jörn-Henrik Jacobsen, Christina Heinze-Deml
2023	A*	`conf`	The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning. ICML Borja Rodríguez Gálvez, Arno Blaas, Pau Rodríguez, Adam Golinski, Xavier Suau, Jason Ramapuram, Dan Busbridge, Luca Zappella
2023	J	`jnl`	The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning. CoRR Borja Rodríguez Gálvez, Arno Blaas, Pau Rodríguez, Adam Golinski, Xavier Suau, Jason Ramapuram, Dan Busbridge, Luca Zappella
2022	J	`jnl`	COIN++: Data Agnostic Neural Compression. CoRR Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Golinski, Yee Whye Teh, Arnaud Doucet
2022	J	`jnl`	COIN++: Neural Compression Across Modalities. Trans. Mach. Learn. Res. Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Golinski, Yee Whye Teh, Arnaud Doucet
2022	A	`conf`	Expectation programming: Adapting probabilistic programming systems to estimate expectations efficiently. UAI Tim Reichelt, Adam Golinski, Luke Ong, Tom Rainforth
2022	A*	`conf`	LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood. ICML Piotr Tempczyk, Rafal Michaluk, Lukasz Garncarek, Przemyslaw Spurek, Jacek Tabor, Adam Golinski
2022	J	`jnl`	LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood. CoRR Piotr Tempczyk, Rafal Michaluk, Lukasz Garncarek, Przemyslaw Spurek, Jacek Tabor, Adam Golinski
2021	J	`jnl`	COIN: COmpression with Implicit Neural representations. CoRR Emilien Dupont, Adam Golinski, Milad Alizadeh, Yee Whye Teh, Arnaud Doucet
2021	J	`jnl`	Expectation Programming. CoRR Tim Reichelt, Adam Golinski, Luke Ong, Tom Rainforth
2020	—	`conf`	Feedback Recurrent Autoencoder for Video Compression. ACCV (4) Adam Golinski, Reza Pourreza, Yang Yang, Guillaume Sautière, Taco S. Cohen
2020	J	`jnl`	Feedback Recurrent Autoencoder for Video Compression. CoRR Adam Golinski, Reza Pourreza, Yang Yang, Guillaume Sautière, Taco S. Cohen
2020	J	`jnl`	Target-Aware Bayesian Inference: How to Beat Optimal Conventional Estimators. J. Mach. Learn. Res. Tom Rainforth, Adam Golinski, Frank Wood, Sheheryar Zaidi
2019	A*	`conf`	Amortized Monte Carlo Integration. ICML Adam Golinski, Frank Wood, Tom Rainforth
2019	J	`jnl`	Amortized Monte Carlo Integration. CoRR Adam Golinski, Frank Wood, Tom Rainforth
2018	A*	`conf`	Faithful Inversion of Generative Models for Effective Amortized Inference. NeurIPS Stefan Webb, Adam Golinski, Robert Zinkov, Siddharth Narayanaswamy, Tom Rainforth, Yee Whye Teh, Frank Wood
2017	J	`jnl`	Faithful Model Inversion Substantially Improves Auto-encoding Variational Inference. CoRR Stefan Webb, Adam Golinski, Robert Zinkov, N. Siddharth, Yee Whye Teh, Frank D. Wood