Beyond Imitation: Generative and Variational Choreography via Machine Learning. - Mariel Pettee; Chase Shimmin; Douglas Duhaime; Ilya Vidrin (ICCC, 2019)

PirouNet: Creating Dance Through Artist-Centric Deep Learning. - Mathilde Papillon; Mariel Pettee; Nina Miolane (ArtsIT, 2022)

Symmetry Group Equivariant Architectures for Physics. - Alexander Bogatskiy; Sanmay Ganguly; Thomas Kipf; Risi Kondor; David W. Miller; Daniel Murnane; Jan T. Offermann; Mariel Pettee; Phiala E. Shanahan; Chase Shimmin; Savannah Thais (CoRR, 2022)

PirouNet: Creating Intentional Dance with Semi-Supervised Conditional Recurrent Variational Autoencoders. - Mathilde Papillon; Mariel Pettee; Nina Miolane (CoRR, 2022)

Intentional Choreography with Semi-Supervised Recurrent VAEs. - Mathilde Papillon; Mariel Pettee; Nina Miolane (CoRR, 2022)

Weakly-Supervised Anomaly Detection in the Milky Way. - Mariel Pettee; Sowmya Thanvantri; Benjamin Nachman; David Shih; Matthew R. Buckley; Jack H. Collins (CoRR, 2023)

xVal: A Continuous Number Encoding for Large Language Models. - Siavash Golkar; Mariel Pettee; Michael Eickenberg; Alberto Bietti; Miles D. Cranmer; Géraud Krawezik; François Lanusse; Michael McCabe; Ruben Ohana; Liam Holden Parker; Bruno Régaldo-Saint Blancard; Tiberiu Tesileanu; et al. (CoRR, 2023)

Multiple Physics Pretraining for Physical Surrogate Models. - Michael McCabe; Bruno Régaldo-Saint Blancard; Liam Holden Parker; Ruben Ohana; Miles D. Cranmer; Alberto Bietti; Michael Eickenberg; Siavash Golkar; Géraud Krawezik; François Lanusse; Mariel Pettee; Tiberiu Tesileanu; et al. (CoRR, 2023)

AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models. - François Lanusse; Liam Holden Parker; Siavash Golkar; Miles D. Cranmer; Alberto Bietti; Michael Eickenberg; Géraud Krawezik; Michael McCabe; Ruben Ohana; Mariel Pettee; Bruno Régaldo-Saint Blancard; Tiberiu Tesileanu; et al. (CoRR, 2023)

Multiple Physics Pretraining for Spatiotemporal Surrogate Models. - Michael McCabe; Bruno Régaldo-Saint Blancard; Liam Holden Parker; Ruben Ohana; Miles D. Cranmer; Alberto Bietti; Michael Eickenberg; Siavash Golkar; Géraud Krawezik; François Lanusse; Mariel Pettee; Tiberiu Tesileanu; et al. (NeurIPS, 2024)

Contextual Counting: A Mechanistic Study of Transformers on a Quantitative Task. - Siavash Golkar; Alberto Bietti; Mariel Pettee; Michael Eickenberg; Miles D. Cranmer; Keiya Hirashima; Géraud Krawezik; Nicholas Lourie; Michael McCabe; Rudy Morel; Ruben Ohana; Liam Holden Parker; et al. (CoRR, 2024)

Dyads: Artist-Centric, AI-Generated Dance Duets. - Zixuan Wang; Luis Zerkowski; Ilya Vidrin; Mariel Pettee (CoRR, 2025)

Invisible Strings: Revealing Latent Dancer-to-Dancer Interactions with Graph Neural Networks. - Luis Vitor Zerkowski; Zixuan Wang; Ilya Vidrin; Mariel Pettee (CoRR, 2025)

What's In Your Field? Mapping Scientific Research with Knowledge Graphs and Large Language Models. - Abhipsha Das; Nicholas Lourie; Siavash Golkar; Mariel Pettee (CoRR, 2025)