Roni Khardon
Computer Science · Indiana University
Publications
127
Citations
2,135
Est. group size
—
Recurring co-author estimate
Active years
32
Publishing since 1994
Roni Khardon works in machine learning and artificial intelligence, developing methods for computers to learn from data, make predictions under uncertainty, and plan sequences of actions. Recent work spans approximate probabilistic inference (estimating uncertainty in models like Bayesian neural networks), automated planning in complex decision spaces, robotic information gathering, and making machine learning models more explainable. The research combines theoretical foundations (such as generalization guarantees and learning theory) with practical applications in robotics and biology.
Publication output has been fairly steady over the last decade, averaging around three per year with a modest peak in 2022-2023.
Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026
- Stability-based Generalization Bounds for Variational Inference
arXiv (Cornell University) · 2025
- Learning DNF through Generalized Fourier Representations
arXiv (Cornell University) · 2025
- Improving planning and MBRL with temporally-extended actions
arXiv (Cornell University) · 2025
- POAM: Probabilistic Online Attentive Mapping for Efficient Robotic Information Gathering
arXiv (Cornell University) · 2024
- POAM: Probabilistic Online Attentive Mapping for Efficient Robotic Information Gathering
2024
- Adaptive Robotic Information Gathering via Non-Stationary Gaussian Processes
arXiv (Cornell University) · 2023
- Adaptive Robotic Information Gathering via non-stationary Gaussian processes
The International Journal of Robotics Research · 2023
- Explainable models via compression of tree ensembles
Machine Learning · 2023
- DiSProD: Differentiable Symbolic Propagation of Distributions for Planning
2023
- Variational Inference on the Final-Layer Output of Neural Networks
arXiv (Cornell University) · 2023
- DiSProD: Differentiable Symbolic Propagation of Distributions for Planning
arXiv (Cornell University) · 2023
- AK: Attentive Kernel for Information Gathering
arXiv (Cornell University) · 2022
- AK: Attentive Kernel for Information Gathering
2022
- On the Performance of Direct Loss Minimization for Bayesian Neural Networks
arXiv (Cornell University) · 2022
- Approximate Inference for Stochastic Planning in Factored Spaces
arXiv (Cornell University) · 2022
- arXiv (Cornell University)×17
- Neural Information Processing Systems×3
- Proceedings of the AAAI Conference on Artificial Intelligence×2
- iScience×1
- The International Journal of Robotics Research×1
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 11, 2026.
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