Aayush Mishra

CoRR, April, 2026

Unsupervised Continual Learning for Amortized Bayesian Inference.

[BibT_eX]

[DOI]

Simon Kucharský

CoRR, February, 2026

BayesFlow 2.0: Multi-Backend Amortized Bayesian Inference in Python.

[BibT_eX]

[DOI]

Stefan T. Radev

CoRR, February, 2026

Genomic Next-Token Predictors are In-Context Learners.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2026

2025

Genomic Next-Token Predictors are In-Context Learners.

[BibT_eX]

[DOI]

CoRR, November, 2025

IA2: Alignment with ICL Activations Improves Supervised Fine-Tuning.

[BibT_eX]

[DOI]

CoRR, September, 2025

Towards Trustworthy Amortized Bayesian Model Comparison.

[BibT_eX]

[DOI]

CoRR, August, 2025

ICL CIPHERS: Quantifying "Learning" in In-Context Learning via Substitution Ciphers.

[BibT_eX]

[DOI]

CoRR, April, 2025

A Critical Review of IoT-Based Structural Health Monitoring for Dams.

[BibT_eX]

[DOI]

IEEE Internet Things J., January, 2025

On the challenges of detecting MCI using EEG in the wild.

[BibT_eX]

[DOI]

Sankara Surendra Telidevara

David Joffe

David S. Oakley

CoRR, January, 2025

Automatic Machine Learning Framework to Study Morphological Parameters of AGN Host Galaxies within z < 1.4 in the Hyper Supreme-Cam Wide Survey.

[BibT_eX]

[DOI]

CoRR, January, 2025

Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled Data.

[BibT_eX]

[DOI]

CoRR, January, 2025

ODD: Overlap-aware Estimation of Model Performance under Distribution Shift.

[BibT_eX]

[DOI]

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

ICL CIPHERS: Quantifying "Learning" in In-Context Learning via Substitution Ciphers.

[BibT_eX]

[DOI]

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Privacy Preserving Ordinal-Meta Learning with VLMs for Fine-Grained Fruit Quality Prediction.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025

2024

Position: Do pretrained Transformers Learn In-Context by Gradient Descent?

[BibT_eX]

[DOI]

Lingfeng Shen

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Source-Free and Image-Only Unsupervised Domain Adaptation for Category Level Object Pose Estimation.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Ordinal-Meta Learning for Fine-Grained Fruit Quality Prediction.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024

2023

Do pretrained Transformers Really Learn In-context by Gradient Descent?

[BibT_eX]

[DOI]

Lingfeng Shen

CoRR, 2023

Stress Testing Chain-of-Thought Prompting for Large Language Models.

[BibT_eX]

[DOI]

Karan Thakkar

CoRR, 2023

DECODE: Data-driven Energy Consumption Prediction leveraging Historical Data and Environmental Factors in Buildings.

[BibT_eX]

[DOI]

Aditya Mishra

Haroon R. Lone

CoRR, 2023

2022

Repeated Environment Inference for Invariant Learning.

[BibT_eX]

[DOI]