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Meetings
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Publications
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Journals
- Neural Synthetic Profiles from Remote Sensing and Observations (NeSPReSO) — Reconstructing temperature and salinity fields in the Gulf of Mexico
- Turbulence Closure with Small, Local Neural Networks: Forced Two-dimensional and β-plane Flows
- Theoretical Tools for Understanding the Climate Crisis from Hasselmann’s Programme and Beyond
- Convolutional Neural Networks for Sea Surface Data Assimilation in Operational Ocean Models: Test Case in the Gulf of Mexico
- Surface Drifter Trajectory Prediction in the Gulf of Mexico Using Neural Networks
- The High-Frequency and Rare Events Barriers to Neural Closures of Atmospheric Dynamics
- Generic Generation of Noise-Driven Chaos in Stochastic Time Delay Systems: Bridging the Gap with High-End Simulations
- Transitions in Stochastic Non-Equilibrium Systems: Efficient Reduction and Analysis
- Optimal Parameterizing Manifolds for Anticipating Tipping Points and Higher-Order Critical Transitions
- Stochastic Rectification of Fast Oscillations on Slow Manifold Closures
- Confidently Comparing Estimates with the c-value
- Deep Reinforcement Learning for Adaptive Mesh Refinement
- Bayesian Learning of Coupled Biogeochemical-Physical Models
- Generalized Neural Closure Models with Interpretability
- Neural Closure Models for Dynamical Systems
- Reduced-order Models for Coupled Dynamical Systems: Data-driven Methods and the Koopman Operator
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Conferences
- Symmetries In-Context: Universal Self-Supervised Learning through Contextual World Models
- On the Hardness of Learning Under Symmetries
- A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs
- Consistent Validation for Predictive Methods in Spatial Settings
- Multi-marginal Schrödinger Bridges with Iterative Reference Refinement
- On Leveraging Pretrained GANs for Generation with Limited Data
- Generalization and Representational Limits of Graph Neural Networks
- Measuring the Robustness of Gaussian Processes to Kernel Choice
- CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
- Measuring Generalization with Optimal Transport
- Gaussian Processes at the Helm(holtz): A More Fluid Model for Ocean Currents
- The Exact Sample Complexity Gain from Invariances for Kernel Regression
- Evaluation of Deep Neural Operator Models toward Ocean Forecasting
- On the Generalization of Learning Algorithms That Do Not Converge
- Neural Closure Model for Dynamic Mode Decomposition Forecasts
- Sparse Regression and Adaptive Feature Generation for the Discovery of Dynamical Systems
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Journals
- Our ML-SCOPE Team