Ricardo Pio Monti

29 papers A* 1A 5Journal 18Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	The Finetuner's Fallacy: When to Pretrain with Your Finetuning Data. CoRR Christina Baek, Ricardo Pio Monti, David Schwab, Amro Abbas, Rishabh Adiga, Cody Blakeney, Maximilian Böther, Paul Burstein, Aldo Gael Carranza, Alvin Deng, Parth Doshi, Vineeth Dorna, Alex Fang, Tony Jiang, Siddharth Joshi, Brett W. Larsen, Jason Chan Lee, Katherine L. Mentzer, Luke Merrick, Haakon Mongstad, Fan Pan, Anshuman Suri, Darren Teh, Jason Telanoff, Jack Urbanek, Zhengping Wang, Josh Wills, Haoli Yin, Aditi Raghunathan, J. Zico Kolter, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt, Pratyush Maini
2026	J	`jnl`	ÜberWeb: Insights from Multilingual Curation for a 20-Trillion-Token Dataset. CoRR Aldo Gael Carranza, Kaleigh Mentzer, Ricardo Pio Monti, Alex Fang, Alvin Deng, Amro Abbas, Anshuman Suri, Brett W. Larsen, Cody Blakeney, Darren Teh, David Schwab, Diego Kiner, Fan Pan, Haakon Mongstad, Haoli Yin, Jack Urbanek, Jason Lee, Jason Telanoff, Josh Wills, Luke Merrick, Maximilian Böther, Parth Doshi, Paul Burstein, Pratyush Maini, Rishabh Adiga, Siddharth Joshi, Spandan Das, Tony Jiang, Vineeth Dorna, Zhengping Wang, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt
2023	J	`jnl`	Identifiability of latent-variable and structural-equation models: from linear to nonlinear. CoRR Aapo Hyvärinen, Ilyes Khemakhem, Ricardo Pio Monti
2022	J	`jnl`	Controllable Generative Modeling via Causal Reasoning. Trans. Mach. Learn. Res. Joey Bose, Ricardo Pio Monti, Aditya Grover
2021	A	`conf`	Causal Autoregressive Flows. AISTATS Ilyes Khemakhem, Ricardo Pio Monti, Robert Leech, Aapo Hyvärinen
2020	J	`jnl`	Autoregressive flow-based causal discovery and inference. CoRR Ricardo Pio Monti, Ilyes Khemakhem, Aapo Hyvärinen
2020	J	`jnl`	Bayesian optimization for automatic design of face stimuli. CoRR Pedro F. Da Costa, Romy Lorenz, Ricardo Pio Monti, Emily J. H. Jones, Robert Leech
2020	J	`jnl`	Causal Autoregressive Flows. CoRR Ilyes Khemakhem, Ricardo Pio Monti, Robert Leech, Aapo Hyvärinen
2020	A*	`conf`	ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA. NeurIPS Ilyes Khemakhem, Ricardo Pio Monti, Diederik P. Kingma, Aapo Hyvärinen
2020	J	`jnl`	ICE-BeeM: Identifiable Conditional Energy-Based Deep Models. CoRR Ilyes Khemakhem, Ricardo Pio Monti, Diederik P. Kingma, Aapo Hyvärinen
2020	A	`conf`	Robust contrastive learning and nonlinear ICA in the presence of outliers. UAI Hiroaki Sasaki, Takashi Takenouchi, Ricardo Pio Monti, Aapo Hyvärinen
2020	A	`conf`	Variational Autoencoders and Nonlinear ICA: A Unifying Framework. AISTATS Ilyes Khemakhem, Diederik P. Kingma, Ricardo Pio Monti, Aapo Hyvärinen
2019	J	`jnl`	Causal Discovery with General Non-Linear Relationships Using Non-Linear ICA. CoRR Ricardo Pio Monti, Kun Zhang, Aapo Hyvärinen
2019	A	`conf`	Causal Discovery with General Non-Linear Relationships using Non-Linear ICA. UAI Ricardo Pio Monti, Kun Zhang, Aapo Hyvärinen
2019	J	`jnl`	Robust contrastive learning and nonlinear ICA in the presence of outliers. CoRR Hiroaki Sasaki, Takashi Takenouchi, Ricardo Pio Monti, Aapo Hyvärinen
2019	J	`jnl`	Towards the interpretation of time-varying regularization parameters in streaming penalized regression models. Pattern Recognit. Lett. Lenka Zbonáková, Ricardo Pio Monti, Wolfgang Karl Härdle
2018	J	`jnl`	A Unified Probabilistic Model for Learning Latent Factors and Their Connectivities from High-Dimensional Data. CoRR Ricardo Pio Monti, Aapo Hyvärinen
2018	A	`conf`	A unified probabilistic model for learning latent factors and their connectivities from high-dimensional data . UAI Ricardo Pio Monti, Aapo Hyvärinen
2018	J	`jnl`	Adaptive regularization for Lasso models in the context of nonstationary data streams. Stat. Anal. Data Min. Ricardo Pio Monti, Christoforos Anagnostopoulos, Giovanni Montana
2018	—	`conf`	Avoiding Degradation in Deep Feed-Forward Networks by Phasing Out Skip-Connections. ICANN (3) Ricardo Pio Monti, Sina Tootoonian, Robin Cao
2017	J	`jnl`	Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods. Frontiers Comput. Neurosci. Ricardo Pio Monti, Romy Lorenz, Peter Hellyer, Robert Leech, Christoforos Anagnostopoulos, Giovanni Montana
2016	J	`jnl`	A framework for adaptive regularization in streaming Lasso models. CoRR Ricardo Pio Monti, Christoforos Anagnostopoulos, Giovanni Montana
2016	—	`conf`	Classifying HCP task-fMRI networks using heat kernels. PRNI Ai Wern Chung, Emanuele Pesce, Ricardo Pio Monti, Giovanni Montana
2016	J	`jnl`	Text-mining the NeuroSynth corpus using Deep Boltzmann Machines. CoRR Ricardo Pio Monti, Romy Lorenz, Robert Leech, Christoforos Anagnostopoulos, Giovanni Montana
2016	—	`conf`	Text-mining the neurosynth corpus using deep boltzmann machines. PRNI Ricardo Pio Monti, Romy Lorenz, Robert Leech, Christoforos Anagnostopoulos, Giovanni Montana
2016	J	`jnl`	The Automatic Neuroscientist: A framework for optimizing experimental design with closed-loop real-time fMRI. NeuroImage Romy Lorenz, Ricardo Pio Monti, Inês R. Violante, Christoforos Anagnostopoulos, Aldo A. Faisal, Giovanni Montana, Robert Leech
2016	—	`conf`	Towards tailoring non-invasive brain stimulation using real-time fMRI and Bayesian optimization. PRNI Romy Lorenz, Ricardo Pio Monti, Adam Hampshire, Yury Koush, Christoforos Anagnostopoulos, Aldo A. Faisal, David J. Sharp, Giovanni Montana, Robert Leech, Inês R. Violante
2015	—	`conf`	Graph Embeddings of Dynamic Functional Connectivity Reveal Discriminative Patterns of Task Engagement in HCP Data. PRNI Ricardo Pio Monti, Romy Lorenz, Peter Hellyer, Robert Leech, Christoforos Anagnostopoulos, Giovanni Montana
2014	J	`jnl`	Estimating time-varying brain connectivity networks from functional MRI time series. NeuroImage Ricardo Pio Monti, Peter Hellyer, David J. Sharp, Robert Leech, Christoforos Anagnostopoulos, Giovanni Montana