Landslide Geohazard Assessment with Convolutional Neural Networks Using Sentinel-2 Imagery Data. - Silvia Liberata Ullo; Maximillian S. Langenkamp; Tuomas P. Oikarinen; Maria Pia del Rosso; Alessandro Sebastianelli; Federica Piccirillo; Stefania Sica (IGARSS, 2019)

Robust Deep Reinforcement Learning through Adversarial Loss. - Tuomas P. Oikarinen; Tsui-Wei Weng; Luca Daniel (CoRR, 2020)

GraphMDN: Leveraging graph structure and deep learning to solve inverse problems. - Tuomas P. Oikarinen; Daniel C. Hannah; Sohrob Kazerounian (IJCNN, 2021)

Robust Deep Reinforcement Learning through Adversarial Loss. - Tuomas P. Oikarinen; Wang Zhang; Alexandre Megretski; Luca Daniel; Tsui-Wei Weng (NeurIPS, 2021)

Corrupting Neuron Explanations of Deep Visual Features. - Divyansh Srivastava; Tuomas P. Oikarinen; Tsui-Wei Weng (ICCV, 2023)

Label-free Concept Bottleneck Models. - Tuomas P. Oikarinen; Subhro Das; Lam M. Nguyen; Tsui-Wei Weng (ICLR, 2023)

CLIP-Dissect: Automatic Description of Neuron Representations in Deep Vision Networks. - Tuomas P. Oikarinen; Tsui-Wei Weng (ICLR, 2023)

Concept-Monitor: Understanding DNN training through individual neurons. - Mohammad Ali Khan; Tuomas P. Oikarinen; Tsui-Wei Weng (CoRR, 2023)

The Importance of Prompt Tuning for Automated Neuron Explanations. - Justin Lee; Tuomas P. Oikarinen; Arjun Chatha; Keng-Chi Chang; Yilan Chen 002; Tsui-Wei Weng (CoRR, 2023)

Linear Explanations for Individual Neurons. - Tuomas P. Oikarinen; Tsui-Wei Weng (ICML, 2024)

Describe-and-Dissect: Interpreting Neurons in Vision Networks with Language Models. - Nicholas Bai; Rahul A. Iyer; Tuomas P. Oikarinen; Tsui-Wei Weng (CoRR, 2024)

Crafting Large Language Models for Enhanced Interpretability. - Chung-En Sun; Tuomas P. Oikarinen; Tsui-Wei Weng (CoRR, 2024)

Concept Bottleneck Language Models For protein design. - Aya Abdelsalam Ismail; Tuomas P. Oikarinen; Amy Wang; Julius Adebayo; Samuel Stanton; Taylor Joren; Joseph Kleinhenz; Allen Goodman; Héctor Corrada Bravo; Kyunghyun Cho; Nathan C. Frey (CoRR, 2024)

Concept-Driven Continual Learning. - Sin-Han Yang; Tuomas P. Oikarinen; Tsui-Wei Weng (Trans. Mach. Learn. Res., 2024)

Interpretable Generative Models through Post-hoc Concept Bottlenecks. - Akshay R. Kulkarni; Ge Yan; Chung-En Sun; Tuomas P. Oikarinen; Tsui-Wei Weng (CVPR, 2025)

Concept Bottleneck Language Models For Protein Design. - Aya Abdelsalam Ismail; Tuomas P. Oikarinen; Amy Wang; Julius Adebayo; Samuel Don Stanton; Héctor Corrada Bravo; Kyunghyun Cho; Nathan C. Frey (ICLR, 2025)

Concept Bottleneck Large Language Models. - Chung-En Sun; Tuomas P. Oikarinen; Berk Ustun; Tsui-Wei Weng (ICLR, 2025)

SAND: Enhancing Open-Set Neuron Descriptions through Spatial Awareness. - Anvita A. Srinivas; Tuomas P. Oikarinen; Divyansh Srivastava; Wei-Hung Weng; Tsui-Wei Weng (WACV, 2025)

Interpreting Neurons in Deep Vision Networks with Language Models. - Nicholas Bai; Rahul A. Iyer; Tuomas P. Oikarinen; Akshay R. Kulkarni; Tsui-Wei Weng (Trans. Mach. Learn. Res., 2025)

Evaluating Neuron Explanations: A Unified Framework with Sanity Checks. - Tuomas P. Oikarinen; Ge Yan; Tsui-Wei Weng (CoRR, 2025)

Rethinking Crowd-Sourced Evaluation of Neuron Explanations. - Tuomas P. Oikarinen; Ge Yan; Akshay R. Kulkarni; Tsui-Wei Weng (CoRR, 2025)