Tommaso Biancalani

According to our database, Tommaso Biancalani authored at least 26 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Building, benchmarking, and exploring perturbative maps of transcriptional and morphological data.

Safiye Celik, Jan-Christian Hütter, Sandra Melo Carlos, Nathan H. Lazar, Rahul Mohan, Conor Tillinghast, Tommaso Biancalani, Marta M. Fay, Berton Earnshaw, Imran S. Haque

PLoS Comput. Biol., 2024

MolCap-Arena: A Comprehensive Captioning Benchmark on Language-Enhanced Molecular Property Prediction.

Carl Edwards, Ziqing Lu, Ehsan Hajiramezanali, Tommaso Biancalani, Heng Ji, Gabriele Scalia

CoRR, 2024

Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design.

Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Tommaso Biancalani, Avantika Lal, Tommi S. Jaakkola, Sergey Levine, Hanchen Wang, Aviv Regev

CoRR, 2024

A mechanistically interpretable neural network for regulatory genomics.

Alex M. Tseng, Gökcen Eraslan, Tommaso Biancalani, Gabriele Scalia

CoRR, 2024

Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding.

Xiner Li, Yulai Zhao, Chenyu Wang, Gabriele Scalia, Gökcen Eraslan, Surag Nair, Tommaso Biancalani, Aviv Regev, Sergey Levine, Masatoshi Uehara

CoRR, 2024

Cell Morphology-Guided Small Molecule Generation with GFlowNets.

Stephen Zhewen Lu, Ziqing Lu, Ehsan Hajiramezanali, Tommaso Biancalani, Yoshua Bengio, Gabriele Scalia, Michal Koziarski

CoRR, 2024

Understanding Reinforcement Learning-Based Fine-Tuning of Diffusion Models: A Tutorial and Review.

Masatoshi Uehara, Yulai Zhao, Tommaso Biancalani, Sergey Levine

CoRR, 2024

Adding Conditional Control to Diffusion Models with Reinforcement Learning.

Yulai Zhao, Masatoshi Uehara, Gabriele Scalia, Tommaso Biancalani, Sergey Levine, Ehsan Hajiramezanali

CoRR, 2024

Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models.

Masatoshi Uehara, Yulai Zhao, Ehsan Hajiramezanali, Gabriele Scalia, Gökcen Eraslan, Avantika Lal, Sergey Levine, Tommaso Biancalani

CoRR, 2024

Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control.

Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Tommaso Biancalani, Sergey Levine

CoRR, 2024

regLM: Designing Realistic Regulatory DNA with Autoregressive Language Models.

Avantika Lal, David Garfield, Tommaso Biancalani, Gökcen Eraslan

Proceedings of the Research in Computational Molecular Biology, 2024

Feedback Efficient Online Fine-Tuning of Diffusion Models.

Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Sergey Levine, Tommaso Biancalani

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Conformalized Deep Splines for Optimal and Efficient Prediction Sets.

Nathaniel Diamant, Ehsan Hajiramezanali, Tommaso Biancalani, Gabriele Scalia

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Unsupervised Segmentation of Colonoscopy Images.

Heming Yao, Jérôme Lüscher, Benjamín Gutiérrez-Becker, Josep Arús-Pous, Tommaso Biancalani, Amelie Bigorgne, David Richmond

CoRR, 2023

Complex Preferences for Different Convergent Priors in Discrete Graph Diffusion.

Alex M. Tseng, Nathaniel Diamant, Tommaso Biancalani, Gabriele Scalia

CoRR, 2023

RINGER: Rapid Conformer Generation for Macrocycles with Sequence-Conditioned Internal Coordinate Diffusion.

Colin A. Grambow, Hayley Weir, Nathaniel L. Diamant, Alex M. Tseng, Tommaso Biancalani, Gabriele Scalia, Kangway V. Chuang

CoRR, 2023

CREMP: Conformer-Rotamer Ensembles of Macrocyclic Peptides for Machine Learning.

Colin A. Grambow, Hayley Weir, Christian N. Cunningham, Tommaso Biancalani, Kangway V. Chuang

CoRR, 2023

GraphGUIDE: interpretable and controllable conditional graph generation with discrete Bernoulli diffusion.

Alex M. Tseng, Nathaniel Diamant, Tommaso Biancalani, Gabriele Scalia

CoRR, 2023

Multitask-Guided Self-Supervised Tabular Learning for Patient-Specific Survival Prediction.

You Wu, Omid Bazgir, Yongju Lee, Tommaso Biancalani, James Lu, Ehsan Hajiramezanali

Proceedings of the Machine Learning in Computational Biology, November 30, 2023

Towards Understanding and Improving GFlowNet Training.

Max W. Shen, Emmanuel Bengio, Ehsan Hajiramezanali, Andreas Loukas, Kyunghyun Cho, Tommaso Biancalani

Proceedings of the International Conference on Machine Learning, 2023

Improving Graph Generation by Restricting Graph Bandwidth.

Nathaniel Lee Diamant, Alex M. Tseng, Kangway V. Chuang, Tommaso Biancalani, Gabriele Scalia

Proceedings of the International Conference on Machine Learning, 2023

NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning.

Muralikrishnna G. Sethuraman, Romain Lopez, Rahul Mohan, Faramarz Fekri, Tommaso Biancalani, Jan-Christian Hütter

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Hierarchically branched diffusion models for efficient and interpretable multi-class conditional generation.

Alex M. Tseng, Tommaso Biancalani, Max M. Shen, Gabriele Scalia

CoRR, 2022

A 3D-Shape Similarity-based Contrastive Approach to Molecular Representation Learning.

Austin Atsango, Nathaniel L. Diamant, Ziqing Lu, Tommaso Biancalani, Gabriele Scalia, Kangway V. Chuang

CoRR, 2022

Conditional Diffusion with Less Explicit Guidance via Model Predictive Control.

Max W. Shen, Ehsan Hajiramezanali, Gabriele Scalia, Alex M. Tseng, Nathaniel Diamant, Tommaso Biancalani, Andreas Loukas

CoRR, 2022

2019

The human body at cellular resolution: the NIH Human Biomolecular Atlas Program.

Michael P. Snyder, Shin Lin, Amanda Posgai, Mark Atkinson, Aviv Regev, Jennifer Rood, Orit Rozenblatt-Rosen, Leslie Gaffney, Anna Hupalowska, Rahul Satija, Nils Gehlenborg, Jay Shendure, Julia Laskin, Pehr Harbury, Nicholas A. Nystrom, Jonathan C. Silverstein, Ziv Bar-Joseph, Kun Zhang, Katy Börner, Yiing Lin, Richard Conroy, Dena Procaccini, Ananda L. Roy, Ajay Pillai, Marishka Brown, Zorina S. Galis, Long Cai, Cole Trapnell, Dana Jackson, Garry P. Nolan, William James Greenleaf, Sylvia K. Plevritis, Sara Ahadi, Stephanie A. Nevins, Hayan Lee, Christian Martijn Schuerch, Sarah Black, Vishal Gautham Venkataraaman, Ed Esplin, Aaron Horning, Amir Bahmani, Xin Sun, Sanjay Jain, James S. Hagood, Gloria Pryhuber, Peter V. Kharchenko, Bernd Bodenmiller, Todd Brusko, Michael Clare-Salzler, Harry Nick, Kevin Otto, Clive Wasserfall, Marda Jorgensen, Maigan Brusko, Sergio Maffioletti, Richard M. Caprioli, Jeffrey M. Spraggins, Danielle Gutierrez, Nathan Heath Patterson, Elizabeth K. Neumann, Raymond Harris, Mark P. de Caestecker, Agnes B. Fogo, Raf Van de Plas, Ken Lau, Guo-Cheng Yuan, Qian Zhu, Ruben Dries, Peng Yin, Sinem K. Saka, Jocelyn Y. Kishi, Yu Wang, Isabel Goldaracena, Dong Hye Ye, Kristin E. Burnum-Johnson, Paul D. Piehowski, Charles Ansong, Ying Zhu, Tushar Desai, Jay Mulye, Peter Chou, Monica Nagendran, Sarah A. Teichmann, Benedict Paten, Robert F. Murphy, Jian Ma, Vladimir Yu. Kiselev, Carl Kingsford, Allyson Ricarte, Maria Keays, Sushma Anand Akoju, Matthew Ruffalo, Margaret Vella, Chuck McCallum, Leonard E. Cross, Samuel H. Friedman, Randy W. Heiland, Bruce William Herr II, Paul Macklin, Ellen M. Quardokus, Lisel Record, James P. Sluka, Griffin M. Weber, Philip D. Blood, Alexander Ropelewski, William Shirey, Robin M. Scibek, Paula M. Mabee, W. Christopher Lenhardt, Kimberly Robasky, Stavros Michailidis, John C. Marioni, Andrew Butler, Tim Stuart, Eyal Fisher, Shila Ghazanfar, Gökcen Eraslan, Tommaso Biancalani, Eeshit D. Vaishnav, Pothur Srinivas, Aaron Pawlyk, Salvatore Sechi, Elizabeth L. Wilder, James Anderson

Nat., 2019