Danielle C. Maddix
10 papers · 2020–2025 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+1 more ↓ Show less ↑
π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (22) π Century Club Β· Bronze
π
Trend Setter
Top co-authors
Research topics
Machine Learning
(10)
Deep Learning
(5)
Artificial Intelligence
(4)
Learning Types Β· Machine Learning
(4)
Data Science & Analytics
(3)
Core AI
(3)
Optimization & Theory
(3)
Architectures
(2)
Core Methods
(2)
Methods
(2)
Application Areas
(1)
Applications
(1)
Bayesian & Probabilistic
(1)
Learning Types Β· Deep Learning
(1)
Models
(1)
Keywords
time series forecasting
(3)
neural operator
(2)
uncertainty quantification
(2)
partial differential equation
(2)
deep learning
(1)
pretraining
(1)
anomaly detection
(1)
computational fluid dynamics
(1)
interpolation
(1)
autoregressive model
(1)
variance reduction
(1)
operator learning
(1)
physics-informed learning
(1)
foundation model
(1)
downstream task
(1)
pre-trained model
(1)
boundary condition
(1)
probabilistic forecasting
(1)
bayesian inference
(1)
regularization
(1)
Papers
ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables
AISTATS 2025
Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization
ICML 2025
Gradient-Free Generation for Hard-Constrained Systems
ICLR 2025
Transferring Knowledge From Large Foundation Models to Small Downstream Models
ICML 2024
Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs
ICML 2024
WindsorML: High-Fidelity Computational Fluid Dynamics Dataset For Automotive Aerodynamics
NeurIPS 2024
Guiding continuous operator learning through Physics-based boundary constraints
ICLR 2023
Learning Physical Models that Can Respect Conservation Laws
ICML 2023
Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting
ICML 2023
GluonTS: Probabilistic and Neural Time Series Modeling in Python
JMLR 2020