Research

All of my publications can be found on my Google Scholar.

Papers

1. LatticeVision: Image to Image Networks for Modeling Non-Stationary Spatial Data
   Antony Sikorski, Michael Ivanitskiy, Nathan Lenssen, Douglas Nychka, Daniel McKenzie
   International Conference on Artificial Intelligence and Statistics (AISTATS), (2026)
   [Paper], [Code]

2. A Non-stationary, Amortized, Transfer Learning Approach for Modeling Italian Air Quality
   Alessandro Fusta Moro, Antony Sikorski, Daniel McKenzie, Alessandro Fassò, Douglas Nychka
   arXiv, (2026)
   [arXiv], [Code]

3. Normalizing Basis Functions: Approximate Stationary Models for Large Spatial Data
   Antony Sikorski, Daniel McKenzie, Douglas Nychka
   Stat, 13(4), e70015, (2024)
   [Paper], [arXiv], [Code]

4. Crystal Growth of Quantum Magnets in the Rare-Earth Pyrosilicate Family R 2Si2O7 (R= Yb, Er) Using the Optical Floating Zone Method
   Harikrishnan S. Nair, Tim DeLazzer, Tim Reeder, Antony Sikorski, Gavin Hester, and Kathryn A. Ross.
   Crystals, 9(4), 196. (2019)
   [Paper]

Posters

1. LatticeVision: Image to Image Networks for Modeling Non-Stationary Spatial Data
   Antony Sikorski, Michael Ivanitskiy, Nathan Lenssen, Douglas Nychka, Daniel McKenzie
   The 29th International Conference on Artificial Intelligence and Statistics (AISTATS) (2026)

2. Basis for Change: Approximate Stationary Models for Large Spatial Data
   Antony Sikorski, Daniel McKenzie, Douglas Nychka
   
   • Joint Statistical Meetings (JSM) (2024)
   • Extremes (2024)
   • International Meeting for Statistical Climatology (IMSC) (2024)
   • Mines Graduate Research and Discovery Symposium (GRADS) (2024)
     PDF, [Link]
3. Optical Floating Zone Growth of Yb2Si2O7
   Antony Sikorski, Harikrishnan S. Nair, Kathryn A. Ross
   APS Four Corners Conference (2017)
   JPG, [Link]

Talks

1. Vision Models for Big, Non-Stationary, Spatial Data
   Antony Sikorski, Michael Ivanitskiy, Daniel McKenzie, Douglas Nychka
   
   • Talk at AMS GVD Research Symposium (2025)
   • Talk at GRADS (The Graduate Research and Discovery Symposium) (2025)

2. Machine Learning for Equation Discovery in Climate Science
   Antony Sikorski
   Invited talk at Mines Optimization and Deep Learning Seminar (MODL) (2024)

3. Parametrizing Turbulent Fluxes in the Planetary Boundary Layer with Symbolic Regression
   Laura Pong, Greta VanZetten, Antony Sikorski, Yongquan Qu, Sara Shamekh
   NY Climate Change @ LEAP (2024)
   PDF

4. Basis for Change: Approximate Stationary Models for Large Spatial Data
   Antony Sikorski, Daniel McKenzie, Douglas Nychka
   
   • Speed Talk at International Meeting for Statistical Climatology (IMSC) (2024)
   • Speed Talk at Extremes (2024)

5. Fast Prediction and Parameter Estimation for Large Spatial Data Volumes with Deep Learning
   Antony Sikorski
   Invited talk at AMS Graduate Student Colloquium (2023)

6. Exploring Neural Likelihood Surfaces for Spatial Processes
   Antony Sikorski
   Mines Optimization and Deep Learning Seminar (MODL) (2023)

7. Networking at Neurips
   Antony Sikorski
   Mines Optimization and Deep Learning Seminar (MODL) (2026)

8. How and Why to get Internships during your PhD
   Antony Sikorski
   AMS Graduate Student Colloquium (2026)