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09/20/2023
When to Trust AI: Advances and Challenges for Certification of Neural Networks
Artificial intelligence (AI) has been advancing at a fast pace and it is...
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06/23/2023
Adversarial Robustness Certification for Bayesian Neural Networks
We study the problem of certifying the robustness of Bayesian neural net...
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05/05/2023
On Preimage Approximation for Neural Networks
Neural network verification mainly focuses on local robustness propertie...
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05/02/2023
Sample Efficient Model-free Reinforcement Learning from LTL Specifications with Optimality Guarantees
Linear Temporal Logic (LTL) is widely used to specify high-level objecti...
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04/17/2023
Compositional Probabilistic and Causal Inference using Tractable Circuit Models
Probabilistic circuits (PCs) are a class of tractable probabilistic mode...
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11/28/2022
Bayesian Network Models of Causal Interventions in Healthcare Decision Making: Literature Review and Software Evaluation
This report summarises the outcomes of a systematic literature search to...
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11/11/2022
Symbolic Verification and Strategy Synthesis for Turn-based Stochastic Games
Stochastic games are a convenient formalism for modelling systems that c...
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10/12/2022
When are Local Queries Useful for Robust Learning?
Distributional assumptions have been shown to be necessary for the robus...
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10/08/2022
Robustness of Unsupervised Representation Learning without Labels
Unsupervised representation learning leverages large unlabeled datasets ...
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06/05/2022
Learning Dynamics and Generalization in Reinforcement Learning
Solving a reinforcement learning (RL) problem poses two competing challe...
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05/12/2022
Sample Complexity Bounds for Robustly Learning Decision Lists against Evasion Attacks
A fundamental problem in adversarial machine learning is to quantify how...
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05/11/2022
Robustness Guarantees for Credal Bayesian Networks via Constraint Relaxation over Probabilistic Circuits
In many domains, worst-case guarantees on the performance (e.g., predict...
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05/11/2022
Individual Fairness Guarantees for Neural Networks
We consider the problem of certifying the individual fairness (IF) of fe...
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04/29/2022
Tractable Uncertainty for Structure Learning
Bayesian structure learning allows one to capture uncertainty over the c...
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01/24/2022
Correlated Equilibria and Fairness in Concurrent Stochastic Games
Game-theoretic techniques and equilibria analysis facilitate the design ...
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12/13/2021
The King is Naked: on the Notion of Robustness for Natural Language Processing
There is growing evidence that the classical notion of adversarial robus...
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11/20/2021
Probabilistic Model Checking and Autonomy
Design and control of autonomous systems that operate in uncertain or ad...
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08/25/2021
Backdoor Attacks on Network Certification via Data Poisoning
Certifiers for neural networks have made great progress towards provable...
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05/21/2021
Certification of Iterative Predictions in Bayesian Neural Networks
We consider the problem of computing reach-avoid probabilities for itera...
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05/19/2021
Provable Guarantees on the Robustness of Decision Rules to Causal Interventions
Robustness of decision rules to shifts in the data-generating process is...
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05/08/2021
On Guaranteed Optimal Robust Explanations for NLP Models
We build on abduction-based explanations for ma-chine learning and devel...
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04/07/2021
Adversarial Robustness Guarantees for Gaussian Processes
Gaussian processes (GPs) enable principled computation of model uncertai...
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02/10/2021
Bayesian Inference with Certifiable Adversarial Robustness
We consider adversarial training of deep neural networks through the len...
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10/01/2020
Assessing Robustness of Text Classification through Maximal Safe Radius Computation
Neural network NLP models are vulnerable to small modifications of the i...
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08/11/2020
Automatic Verification of Concurrent Stochastic Systems
Automated verification techniques for stochastic games allow formal reas...
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07/07/2020
Multi-player Equilibria Verification for Concurrent Stochastic Games
Concurrent stochastic games (CSGs) are an ideal formalism for modelling ...
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05/01/2020
On the Benefits of Invariance in Neural Networks
Many real world data analysis problems exhibit invariant structure, and ...
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04/21/2020
Probabilistic Safety for Bayesian Neural Networks
We study probabilistic safety for Bayesian Neural Networks (BNNs) under ...
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03/12/2020
Invariant Causal Prediction for Block MDPs
Generalization across environments is critical to the successful applica...
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11/29/2019
Safety Guarantees for Planning Based on Iterative Gaussian Processes
Gaussian Processes (GPs) are widely employed in control and learning bec...
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09/21/2019
Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control
Deep neural network controllers for autonomous driving have recently ben...
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09/12/2019
On the Hardness of Robust Classification
It is becoming increasingly important to understand the vulnerability of...
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07/22/2019
Correct-by-Construction Advanced Driver Assistance Systems based on a Cognitive Architecture
Research into safety in autonomous and semi-autonomous vehicles has, so ...
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06/28/2019
Robustness Guarantees for Deep Neural Networks on Videos
The widespread adoption of deep learning models places demands on their ...
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06/21/2019
Verification and Control of Turn-Based Probabilistic Real-Time Games
Quantitative verification techniques have been developed for the formal ...
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05/28/2019
Robustness Quantification for Classification with Gaussian Processes
We consider Bayesian classification with Gaussian processes (GPs) and de...
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05/16/2019
Reasoning about Cognitive Trust in Stochastic Multiagent Systems
We consider the setting of stochastic multiagent systems modelled as sto...
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04/01/2019
Robustness of 3D Deep Learning in an Adversarial Setting
Understanding the spatial arrangement and nature of real-world objects i...
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03/05/2019
Statistical Guarantees for the Robustness of Bayesian Neural Networks
We introduce a probabilistic robustness measure for Bayesian Neural Netw...
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12/18/2018
Safety and Trustworthiness of Deep Neural Networks: A Survey
In the past few years, significant progress has been made on deep neural...
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11/17/2018
Equilibria-based Probabilistic Model Checking for Concurrent Stochastic Games
Probabilistic model checking for stochastic games enables formal verific...
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11/16/2018
Evaluating Uncertainty Quantification in End-to-End Autonomous Driving Control
A rise in popularity of Deep Neural Networks (DNNs), attributed to more ...
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09/17/2018
Robustness Guarantees for Bayesian Inference with Gaussian Processes
Bayesian inference and Gaussian processes are widely used in application...
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07/10/2018
A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees
Despite the improved accuracy of deep neural networks, the discovery of ...
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05/06/2018
Reachability Analysis of Deep Neural Networks with Provable Guarantees
Verifying correctness of deep neural networks (DNNs) is challenging. We ...
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04/30/2018
Concolic Testing for Deep Neural Networks
Concolic testing alternates between CONCrete program execution and symbO...
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04/23/2018
Central Limit Model Checking
We consider probabilistic model checking for continuous-time Markov chai...
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04/16/2018
Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for L0 Norm
Deployment of deep neural networks (DNNs) in safety or security-critical...
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10/22/2017
Experimental Biological Protocols with Formal Semantics
Both experimental and computational biology is becoming increasingly aut...
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10/21/2017
