Spectral DefocusCam: Compressive Hyperspectral Imaging from Defocus Measurements. - Georgia Channing (AAAI, 2022)

A Methodology to Generate Efficient Neural Networks for Classification of Scientific Datasets. - Ria Patel; Ariel Keller Rorabaugh; Paula Olaya; Silvina Caíno-Lores; Georgia Channing; Catherine D. Schuman; Osamu Miyashita; Florence Tama; Michela Taufer (e-Science, 2022)

VINARCH: A Visual Analytics Interactive Tool for Neural Network Archaeology. - Seoyoung An; Georgia Channing; Catherine D. Schuman; Michela Taufer (CLUSTER Workshops, 2023)

Composable Workflow for Accelerating Neural Architecture Search Using In Situ Analytics for Protein Classification. - Georgia Channing; Ria Patel; Paula Olaya; Ariel Keller Rorabaugh; Osamu Miyashita; Silvina Caíno-Lores; Catherine D. Schuman; Florence Tama; Michela Taufer (ICPP, 2023)

Toward Robust Real-World Audio Deepfake Detection: Closing the Explainability Gap. - Georgia Channing; Juil Sock; Ronald Clark; Philip Torr 001; Christian Schröder de Witt (CoRR, 2024)

PSyDUCK: Training-Free Steganography for Latent Diffusion. - Georgia Channing; Aqib Mahfuz; Mark van der Wilk; Philip Torr 001; Fabio Pizzati; Christian Schröder de Witt (CoRR, 2025)

Fact-Checking with Contextual Narratives: Leveraging Retrieval-Augmented LLMs for Social Media Analysis. - Arka Ujjal Dey; Muhammad Junaid Awan; Georgia Channing; Christian Schröder de Witt; John P. Collomosse (CoRR, 2025)

AI for Scientific Discovery is a Social Problem. - Georgia Channing; Avijit Ghosh (CoRR, 2025)

LeMat-Synth: a multi-modal toolbox to curate broad synthesis procedure databases from scientific literature. - Magdalena Lederbauer; Siddharth Betala; Xiyao Li; Ayush Jain; Amine Sehaba; Georgia Channing; Grégoire Germain; Anamaria Leonescu; Faris Flaifil; Alfonso Amayuelas; Alexandre Nozadze; Stefan P. Schmid; et al. (CoRR, 2025)