Scalia, Gabriele

31 publications

ICLR 2026 A Joint Diffusion Model with Pre-Trained Priors for RNA Sequence-Structure Co-Design Xiner Li, Masatoshi Uehara, Xingyu Su, Gabriele Scalia, Shuiwang Ji

ICLR 2026 Iterative Distillation for Reward-Guided Fine-Tuning of Diffusion Models in Biomolecular Design Xingyu Su, Xiner Li, Masatoshi Uehara, Sunwoo Kim, Yulai Zhao, Gabriele Scalia, Ehsan Hajiramezanali, Tommaso Biancalani, Degui Zhi, Shuiwang Ji

ICLR 2025 Adding Conditional Control to Diffusion Models with Reinforcement Learning Yulai Zhao, Masatoshi Uehara, Gabriele Scalia, Sunyuan Kung, Tommaso Biancalani, Sergey Levine, Ehsan Hajiramezanali

NeurIPS 2025 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, Shuiwang Ji, Aviv Regev, Sergey Levine, Masatoshi Uehara

ICLRW 2025 Efficient Fine-Tuning of Single-Cell Foundation Models Enables Zero-Shot Molecular Perturbation Prediction Sepideh Maleki, Jan-Christian Huetter, David Richmond, Kangway V. Chuang, Gabriele Scalia, Tommaso Biancalani

ICLRW 2025 MolCap-Arena: A Comprehensive Captioning Benchmark on Language-Enhanced Molecular Property Prediction Carl Edwards, Ziqing Lu, Ehsan Hajiramezanali, Tommaso Biancalani, Heng Ji, Gabriele Scalia

ICLRW 2025 RAG-Enhanced Collaborative LLM Agents for Drug Discovery Namkyeong Lee, Edward De Brouwer, Ehsan Hajiramezanali, Tommaso Biancalani, Chanyoung Park, Gabriele Scalia

ICLRW 2025 Uncovering BioLOGICAL Motifs and Syntax via Sufficient and Necessary Explanations Beepul Bharti, Gabriele Scalia, Tommaso Biancalani, Alex M Tseng

ICLRW 2024 A Mechanistically Interpretable Neural-Network Architecture for Discovery of Regulatory Genomics Alex M Tseng, Gökcen Eraslan, Nathaniel Lee Diamant, Tommaso Biancalani, Gabriele Scalia

NeurIPS 2024 Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models Masatoshi Uehara, Yulai Zhao, Ehsan Hajiramezanali, Gabriele Scalia, Gokcen Eraslan, Avantika Lal, Sergey Levine, Tommaso Biancalani

ICMLW 2024 Cell Morphology-Guided Small Molecule Generation with GFlowNets Stephen Zhewen Lu, Ziqing Lu, Ehsan Hajiramezanali, Tommaso Biancalani, Yoshua Bengio, Gabriele Scalia, Michał Koziarski

ICMLW 2024 Cell Morphology-Guided Small Molecule Generation with GFlowNets Stephen Zhewen Lu, Ziqing Lu, Ehsan Hajiramezanali, Tommaso Biancalani, Yoshua Bengio, Gabriele Scalia, Michał Koziarski

ICMLW 2024 Cell Morphology-Guided Small Molecule Generation with GFlowNets Stephen Zhewen Lu, Ziqing Lu, Ehsan Hajiramezanali, Tommaso Biancalani, Yoshua Bengio, Gabriele Scalia, Michał Koziarski

AISTATS 2024 Conformalized Deep Splines for Optimal and Efficient Prediction Sets Nathaniel Diamant, Ehsan Hajiramezanali, Tommaso Biancalani, Gabriele Scalia

NeurIPSW 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, Shuiwang Ji, Aviv Regev, Sergey Levine, Masatoshi Uehara

ICML 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

NeurIPS 2024 GFlowNet Assisted Biological Sequence Editing Pouya M. Ghari, Alex M. Tseng, Gökcen Eraslan, Romain Lopez, Tommaso Biancalani, Gabriele Scalia, Ehsan Hajiramezanali

TMLR 2024 Hierarchically Branched Diffusion Models Leverage Dataset Structure for Class-Conditional Generation Alex M Tseng, Max W Shen, Tommaso Biancalani, Gabriele Scalia

NeurIPSW 2024 Learning Multi-Cellular Representations of Single-Cell Transcriptomics Data Enables Characterization of Patient-Level Disease States Tianyu Liu, Edward De Brouwer, Tony Kuo, Nathaniel Lee Diamant, Missarova Alsu, Minsheng Hao, Hanchen, Hector Corrada Bravo, Gabriele Scalia, Aviv Regev, Graham Heimberg

TMLR 2024 Score-Based Explainability for Graph Representations Ehsan Hajiramezanali, Sepideh Maleki, Max W Shen, Kangway V. Chuang, Tommaso Biancalani, Gabriele Scalia

ICMLW 2023 Complex Preferences for Different Convergent Priors in Discrete Graph Diffusion Alex M Tseng, Nathaniel Lee Diamant, Tommaso Biancalani, Gabriele Scalia

NeurIPSW 2023 Generative Flow Networks Assisted Biological Sequence Editing Pouya M. Ghari, Alex Tseng, Gökcen Eraslan, Romain Lopez, Tommaso Biancalani, Gabriele Scalia, Ehsan Hajiramezanali

ICLRW 2023 GraphGUIDE: Interpretable and Controllable Conditional Graph Generation with Discrete Bernoulli Diffusion Alex M Tseng, Nathaniel Lee Diamant, Tommaso Biancalani, Gabriele Scalia

ICML 2023 Improving Graph Generation by Restricting Graph Bandwidth Nathaniel Lee Diamant, Alex M Tseng, Kangway V. Chuang, Tommaso Biancalani, Gabriele Scalia

ICLRW 2023 Improving Graph Generation by Restricting Graph Bandwidth Nathaniel Lee Diamant, Alex M Tseng, Kangway V Chuang, Tommaso Biancalani, Gabriele Scalia

ICMLW 2023 Learning to Explain Hypergraph Neural Networks Sepideh Maleki, Ehsan Hajiramezanali, Gabriele Scalia, Tommaso Biancalani, Kangway V. Chuang

NeurIPSW 2023 On the Consistency of GNN Explainability Methods Ehsan Hajiramezanali, Sepideh Maleki, Alex Tseng, Aicha BenTaieb, Gabriele Scalia, Tommaso Biancalani

NeurIPSW 2023 On the Consistency of GNN Explainability Methods Ehsan Hajiramezanali, Sepideh Maleki, Alex Tseng, Aicha BenTaieb, Gabriele Scalia, Tommaso Biancalani

NeurIPSW 2022 A 3D-Shape Similarity-Based Contrastive Approach to Molecular Representation Learning Austin Atsango, Nathaniel Lee Diamant, Ziqing Lu, Tommaso Biancalani, Gabriele Scalia, Kangway V Chuang

NeurIPSW 2022 Deep Fitness Inference for Drug Discovery with Directed Evolution Nathaniel Lee Diamant, Ziqing Lu, Christina Helmling, Kangway V Chuang, Christian Cunningham, Tommaso Biancalani, Gabriele Scalia, Max W Shen

NeurIPSW 2022 STab: Self-Supervised Learning for Tabular Data Ehsan Hajiramezanali, Nathaniel Lee Diamant, Gabriele Scalia, Max W Shen