Tootfinder

EgoBridge: Domain Adaptation for Generalizable Imitation from Egocentric Human Data
Ryan Punamiya, Dhruv Patel, Patcharapong Aphiwetsa, Pranav Kuppili, Lawrence Y. Zhu, Simar Kareer, Judy Hoffman, Danfei Xu
https://arxiv.org/abs/2509.19626

EgoBridge: Domain Adaptation for Generalizable Imitation from Egocentric Human Data
Egocentric human experience data presents a vast resource for scaling up end-to-end imitation learning for robotic manipulation. However, significant domain gaps in visual appearance, sensor modalities, and kinematics between human and robot impede knowledge transfer. This paper presents EgoBridge, a unified co-training framework that explicitly aligns the policy latent spaces between human and robot data using domain adaptation. Through a measure of discrepancy on the joint policy latent featu…

Numeric, which automates accounting workflows, raised a $51M Series B led by IVP, bringing its total funding to $89M, and says OpenAI and Brex are clients (Ryan Lawler/Axios)
https://www.axios.com/pro/fintech-deals/2025/11/19/numeric-51-million-acc…

Exclusive: Numeric raises $51M to automate accounting
Company connects close, cash and analytics in one data layer.

Ugh, listening to Kathryn Ryan on RNZ NineToNoon interviewing Sonny Taite(?) about an 'AI' scribe to take hospital staff clinical notes. Why - oh why - doesn't she ask the important question: where does the data go?! Which jurisdiction? Who's storing it? Who has access? Who cares for it and maintains its security & integrity? Her producers miss it every bloody time. Very disappointing.

Edge-to-Cloud Computations-as-a-Service in Software-Defined Energy Networks for Smart Grids
Jack Jackman, David Ryan, Arun Narayanan, Pedro Nardelli, Indrakshi Dey
https://arxiv.org/abs/2510.11286

Edge-to-Cloud Computations-as-a-Service in Software-Defined Energy Networks for Smart Grids
Modern power grids face an acute mismatch between where data is generated and where it can be processed: protection relays, EV (Electric Vehicle) charging, and distributed renewables demand millisecond analytics at the edge, while energy-hungry workloads often sit in distant clouds leading to missed real-time deadlines and wasted power. We address this by proposing, to our knowledge, the first-ever SDEN (Software Defined Energy Network) for CaaS (Computations-as-a-Service) that unifies edge, fo…

The LCLStream Ecosystem for Multi-Institutional Dataset Exploration
David Rogers, Valerio Mariani, Cong Wang, Ryan Coffee, Wilko Kroeger, Murali Shankar, Hans Thorsten Schwander, Tom Beck, Fr\'ed\'eric Poitevin, Jana Thayer
https://arxiv.org/abs/2510.04012

The LCLStream Ecosystem for Multi-Institutional Dataset Exploration
We describe a new end-to-end experimental data streaming framework designed from the ground up to support new types of applications -- AI training, extremely high-rate X-ray time-of-flight analysis, crystal structure determination with distributed processing, and custom data science applications and visualizers yet to be created. Throughout, we use design choices merging cloud microservices with traditional HPC batch execution models for security and flexibility. This project makes a unique con…

Reanalysis of the eclipses of LHS 1140 c: No evidence of an atmosphere and implications for the internal structure of the planet
Alexandra Rochon, \'Etienne Artigau, Drew Weisserman, Lisa Dang, Ren\'e Doyon, Charles Cadieux, Ryan Cloutier
https://arxiv.org/abs/2510.11397

Reanalysis of the eclipses of LHS 1140 c: No evidence of an atmosphere and implications for the internal structure of the planet
We present the reanalysis of three 15 micron JWST/MIRI secondary eclipses of LHS 1140 c, a warm super-Earth (R$_{\rm{p}}$ = 1.272 R$_{\oplus}$) in a 3.78-day orbit around an M4.5 dwarf. We present a novel method for data reduction that leverages spatial derivatives of the point-spread function and compare it to widely used aperture photometry. Both methods yield eclipse depth consistent within 1 sigma of the values reported in the literature. We measure an eclipse depth of 271$^{+31}_{-30}$ ppm…

Foundation Models for Astrobiology: Paper I -- Workshop and Overview
Ryan Felton, Caleb Scharf, Stuart Bartlett, Nathalie A. Cabrol, Victoria Da Poian, Diana Gentry, Jian Gong, Adrienne Hoarfrost, Manil Maskey, Floyd Nichols, Conor A. Nixon, Tejas Panambur, Joseph Pasterski, Anton S. Petrov, Anirudh Prabhu, Brenda Thomson, Hamed Valizadegan, Kimberley Warren-Rhodes, David Wettergreen, Michael L. Wong, Anastasia Yanchilina

Foundation Models for Astrobiology: Paper I -- Workshop and Overview
Advances in machine learning over the past decade have resulted in a proliferation of algorithmic applications for encoding, characterizing, and acting on complex data that may contain many high dimensional features. Recently, the emergence of deep-learning models trained across very large datasets has created a new paradigm for machine learning in the form of Foundation Models. Foundation Models are programs trained on very large and broad datasets with an extensive number of parameters. Once …

A path towards AI-scale, interoperable biological data
Brian Aevermann, Andrea Califano, Chi-Li Chiu, Nathan Clack, William M. Clemons Jr., Jonah Cool Florence D. D'Orazi, Joseph L. DeRisi, Joshua E. Elias, Elizabeth Fahsbender, Scott E. Fraser, Carlos G. Gonzalez, Matthias Haury, Theofanis Karaletsos, Shana O. Kelley, Aly A. Khan, Alan R. Lowe, Emma Lundberg, Ryan A. McClure, Stephani Otte, Evan O. Paull, Lo\"ic A. Royer, Dana Sadgat, Sandra L. Schmid, Samantha Scovanner, Cat…

A path towards AI-scale, interoperable biological data
Biology is at the precipice of a new era where AI accelerates and amplifies the ability to study how cells operate, organize, and work as systems, revealing why disease happens and how to correct it. Organizations globally are prioritizing AI to accelerate basic research, drug discovery, personalized medicine, and synthetic biology. However, despite these opportunities, scientific data have proven a bottleneck, and progress has been slow and fragmented. Unless the scientific community takes a t…

PDRs4All XVII: Formation and excitation of HD in photodissociation regions. Application to the Orion Bar
Marion Zannese, Jacques Le Bourlot, Evelyne Roueff, Emeric Bron, Franck Le Petit, Dries Van De Putte, Maryvonne Gerin, Naslim Neelamkodan, Javier R. Goicoechea, John Black, Ryan Chown, Ameek Sidhu, Emilie Habart, Els Peeters, Olivier Bern\'e
https://

PDRs4All XVII: Formation and excitation of HD in photodissociation regions. Application to the Orion Bar
The James Webb Space Telescope enabled the first detection of several rovibrational emission lines of HD in the Orion Bar, a prototypical photodissociation region. This provides an incentive to examine the physics of HD in dense and strong PDRs. Using the latest data available on HD excitation by collisional, radiative and chemical processes, our goal is to unveil HD formation and excitation processes in PDRs by comparing our state-of-the-art PDR model with observations made in the Orion Bar an…

Distinguishability of causal structures under latent confounding and selection
Ryan Carey, Marina Maciel Ansanelli, Elie Wolfe, Robin J. Evans
https://arxiv.org/abs/2509.20433 h…

Distinguishability of causal structures under latent confounding and selection
Statistical relationships in observed data can arise for several different reasons: the observed variables may be causally related, they may share a latent common cause, or there may be selection bias. Each of these scenarios can be modelled using different causal graphs. Not all such causal graphs, however, can be distinguished by experimental data. In this paper, we formulate the equivalence class of causal graphs as a novel graphical structure, the selected-marginalized directed graph (smDG)…

GRB 250702B: Discovery of a Gamma-Ray Burst from a Black Hole Falling into a Star
Eliza Neights, Eric Burns, Chris L. Fryer, Dmitry Svinkin, Suman Bala, Rachel Hamburg, Ramandeep Gill, Michela Negro, Megan Masterson, James DeLaunay, David J. Lawrence, Sophie E. D. Abrahams, Yuta Kawakubo, Paz Beniamini, Christian Aa. Diget, Dmitry Frederiks, John Goldsten, Adam Goldstein, Alexander D. Hall-Smith, Erin Kara, Alison M. Laird, Gavin P. Lamb, Oliver J. Roberts, Ryan Seeb, V. Ashley Villar,…

GRB 250702B: Discovery of a Gamma-Ray Burst from a Black Hole Falling into a Star
Gamma-ray bursts are the most luminous electromagnetic events in the universe. Their prompt gamma-ray emission has typical durations between a fraction of a second and several minutes. A rare subset of these events have durations in excess of a thousand seconds, referred to as ultra-long gamma-ray bursts. Here, we report the discovery of the longest gamma-ray burst ever seen with a ~25,000 s gamma-ray duration, GRB 250702B, and characterize this event using data from four instruments in the Int…

Masses, Star-Formation Efficiencies, and Dynamical Evolution of 18,000 HII Regions
Debosmita Pathak, Adam K. Leroy, Ashley. T. Barnes, Todd A. Thompson, Laura A. Lopez, Karin M. Sandstrom, Jiayi Sun, Simon C. O. Glover, Ralf S. Klessen, Eric W. Koch, Kirsten L. Larson, Janice Lee, Sharon Meidt, Patricia Sanchez-Blazquez, Eva Schinnerer, Zein Bazzi, Francesco Belfiore, M\'ed\'eric Boquien, Ryan Chown, Dario Colombo, Enrico Congiu, Oleg V. Egorov, Cosima Eibensteiner, Sushma Kura…

Masses, Star-Formation Efficiencies, and Dynamical Evolution of 18,000 HII Regions
We present measurements of the masses associated with $\sim18,000$ HII regions across 19 nearby star-forming galaxies by combining data from JWST, HST, MUSE, ALMA, VLA, and MeerKAT from the multi-wavelength PHANGS survey. We report 10 pc-scale measurements of the mass of young stars, ionized gas, and older disk stars coincident with each HII region, as well as the initial and current mass of molecular gas, atomic gas, and swept-up shell material, estimated from lower resolution data. We find th…

SDSS-C4 3028: The Nearest Blue Galaxy Cluster Devoid of an Intracluster Medium
Shweta Jain, Yuanyuan Su, Andra Stroe, Paul Nulsen, Hyejeon Cho, Kim HyeongHan, M. James Jee, Ralph P. Kraft, Scott Randall, Jimmy A. Irwin, Ryan L. Sanders, Christine Jones
https://arxiv.org/abs/2509.22523

SDSS-C4 3028: The Nearest Blue Galaxy Cluster Devoid of an Intracluster Medium
SDSS-C4 3028 is a galaxy cluster at $z=0.061$, notable for its unusually high fraction of star-forming galaxies with 19 star-forming and 11 quiescent spectroscopically-confirmed member galaxies. From Subaru/HSC imaging, we derived a weak lensing mass of $M_{200} = (1.3 \pm 0.9) \times 10^{14} \rm M_\odot$, indicating a low-mass cluster. This is in excellent agreement with its dynamical mass of $M_{200} = (1.0\pm0.4)\times10^{14} \rm M_\odot$, derived from SDSS spectroscopic data. XMM-Newton obs…