Map Home
Type / to search with text or keywords
/
keyboard shortcut: Type "/" on your keyboard for a quick search
Search button
Loading...
Loading...
Scroll left
Grants
Citations
H-Index
Patents
News
Books
Scroll right
Collapse sidebar
Data issues & feedback
Adjust height of sidebar
KMap
People
Adjust height of sidebar
KMap
Profile
Jason Pacheco
Assistant Professor, Computer Science | Member of the Graduate Faculty
Computer Science
Overview
Research
More
Collaboration
(2)
Larry Head
Mutual work: 1 Proposal﹒1 Grant
Collaboration Details
Ellen Riloff
Mutual work: 1 Supervisor
Collaboration Details
Grants
(6)
Inference Methods for use with Simulation Models
Active
·
2024
·
$38.5K
·
External
Principal Investigator (PI)
inference methods,
simulation models,
statistical inference,
simulation methods,
computational modeling
Development of Inference Capabilities for 1D and 3D Material Simulation Models
Active
·
2023
·
$37.1K
·
External
Principal Investigator (PI)
material simulation,
inference,
1d modeling,
3d modeling,
development
Robust Maximum Entropy Planning, Learning and Control in Uncertain Environments
Active
·
2022
·
$283.9K
·
External
Principal Investigator (PI)
planning,
learning,
control,
uncertainty,
entropy
Estimation of Stochastic Surface and Region Growth from Temporally Sparse and Spatially Dense Geophysical Data
2021
·
$60K
·
External
Principal Investigator (PI)
stochastic modeling,
geophysical data analysis,
spatial-temporal analysis,
surface growth,
region growth
Estimation of Stochastic Surface and Region Growth from Temporally Sparse and Spatially Dense Geophysical Data
2021
·
$60K
·
External
Principal Investigator (PI)
geophysical data,
stochastic processes,
surface growth,
region growth,
temporal-spatial analysis
Page 1 of 2
Previous page
Next page
Publications
(19)
Recent
Fast Variational Estimation of Mutual Information for Implicit and Explicit Likelihood Models
2023
information theory,
variational inference,
likelihood models,
estimation,
implicit models
An Adversarial Reinforcement Learning Framework for Robust Machine Learning-based Malware Detection
2022
reinforcement learning,
malware detection,
adversarial learning,
machine learning,
robust framework
EW-Tune: A Framework for Privately Fine-Tuning Large Language Models with Differential Privacy
2022
language models,
differential privacy,
framework,
fine-tuning,
privacy
Binary black-box attacks against static malware detectors with reinforcement learning in discrete action spaces
2021
malware detection,
reinforcement learning,
adversarial attacks,
black-box attacks,
static analysis
How probabilistic electricity demand forecasts can expedite universal access to clean and reliable electricity
2021
electricity demand,
clean energy,
probabilistic forecasting,
universal access,
reliable electricity
Nonparametric object and parts modeling with lie groudynamics
2020
nonparametric modeling,
object modeling,
parts modeling,
lie group dynamics,
machine learning
Sequential bayesian experimental design with variable cost structure
2020
bayesian methods,
experimental design,
cost optimization,
sequential decision making,
variable cost
Lightweight Data Fusion with Conjugate Mappings
2020
data fusion,
conjugate mappings,
lightweight,
data integration,
information retrieval
How vision governs the collective behaviour of dense cycling pelotons
2019
vision,
collective behavior,
cycling pelotons,
governance,
behavioral dynamics
Variational information planning for sequential decision making
2019
variational inference,
sequential decision making,
information theory,
optimal control,
reinforcement learning