Daniel Kienitz

Publication Activity (10 Years)

Years Active: 2019-2023
Publications (10 Years): 9

Top Topics

Intrinsic Dimensionality

Natural Language Understanding

Machine Learning

Top Venues

Publications

Marco Casadio, Luca Arnaboldi, Matthew L. Daggitt, Omri Isac, Tanvi Dinkar, Daniel Kienitz, Verena Rieser, Ekaterina Komendantskaya
ANTONIO: Towards a Systematic Method of Generating NLP Benchmarks for Verification. FoMLAS@CAV (2023)
Marco Casadio, Luca Arnaboldi, Matthew L. Daggitt, Omri Isac, Tanvi Dinkar, Daniel Kienitz, Verena Rieser, Ekaterina Komendantskaya
ANTONIO: Towards a Systematic Method of Generating NLP Benchmarks for Verification. CoRR (2023)
Daniel Kienitz, Ekaterina Komendantskaya, Michael A. Lones
The Effect of Manifold Entanglement and Intrinsic Dimensionality on Learning. AAAI (2022)
Marco Casadio, Ekaterina Komendantskaya, Verena Rieser, Matthew L. Daggitt, Daniel Kienitz, Luca Arnaboldi, Wen Kokke
Why Robust Natural Language Understanding is a Challenge. CoRR (2022)
Daniel Kienitz, Ekaterina Komendantskaya, Michael A. Lones
Comparing Complexities of Decision Boundaries for Robust Training: A Universal Approach. ACCV (6) (2022)
Marco Casadio, Matthew L. Daggitt, Ekaterina Komendantskaya, Wen Kokke, Daniel Kienitz, Rob Stewart
Property-driven Training: All You (N)Ever Wanted to Know About. CoRR (2021)
Ekaterina Komendantskaya, Wen Kokke, Daniel Kienitz
Continuous Verification of Machine Learning: a Declarative Programming Approach. PPDP (2020)
Wen Kokke, Ekaterina Komendantskaya, Daniel Kienitz, Robert Atkey, David Aspinall
Neural Networks, Secure by Construction - An Exploration of Refinement Types. APLAS (2020)
Ekaterina Komendantskaya, Rob Stewart, Kirsty Duncan, Daniel Kienitz, Pierre Le Hen, Pascal Bacchus
Neural Network Verification for the Masses (of AI graduates). CoRR (2019)