Computer vision-based recognition of liquid surfaces and phase boundaries in transparent vessels, with emphasis on chemistry applications. - Sagi Eppel; Tal Kachman (CoRR, 2014)

Tracing the boundaries of materials in transparent vessels using computer vision. - Sagi Eppel (CoRR, 2015)

Using curvature to distinguish between surface reflections and vessel contents in computer vision based recognition of materials in transparent vessels. - Sagi Eppel (CoRR, 2015)

Tracing liquid level and material boundaries in transparent vessels using the graph cut computer vision approach. - Sagi Eppel (CoRR, 2016)

Setting an attention region for convolutional neural networks using region selective features, for recognition of materials within glass vessels. - Sagi Eppel (CoRR, 2017)

Hierarchical semantic segmentation using modular convolutional neural networks. - Sagi Eppel (CoRR, 2017)

Classifying a specific image region using convolutional nets with an ROI mask as input. - Sagi Eppel (CoRR, 2018)

Class-independent sequential full image segmentation, using a convolutional net that finds a segment within an attention region, given a pointer pixel within this segment. - Sagi Eppel (CoRR, 2019)

Generator evaluator-selector net: a modular approach for panoptic segmentation. - Sagi Eppel; Alán Aspuru-Guzik (CoRR, 2019)

Seeing Glass: Joint Point-Cloud and Depth Completion for Transparent Objects. - Haoping Xu; Yi Ru Wang; Sagi Eppel; Alán Aspuru-Guzik; Florian Shkurti; Animesh Garg (CoRL, 2021)

Computer vision for liquid samples in hospitals and medical labs using hierarchical image segmentation and relations prediction. - Sagi Eppel; Haoping Xu; Alán Aspuru-Guzik (CoRR, 2021)

Predicting 3D shapes, masks, and properties of materials, liquids, and objects inside transparent containers, using the TransProteus CGI dataset. - Sagi Eppel; Haoping Xu; Yi Ru Wang; Alán Aspuru-Guzik (CoRR, 2021)

Deep molecular dreaming: inverse machine learning for de-novo molecular design and interpretability with surjective representations. - Cynthia Shen; Mario Krenn; Sagi Eppel; Alán Aspuru-Guzik (Mach. Learn. Sci. Technol., 2021)

Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network. - Mario Krenn; Lorenzo Buffoni; Bruno C. Coutinho; Sagi Eppel; Jacob Gates Foster; Andrew Gritsevskiy; Harlin Lee; Yichao Lu; João P. Moutinho; Nima Sanjabi; Rishi Sonthalia; Ngoc Mai Tran; et al. (CoRR, 2022)

One-shot recognition of any material anywhere using contrastive learning with physics-based rendering. - Manuel S. Drehwald; Sagi Eppel; Jolina Li; Han Hao; Alán Aspuru-Guzik (ICCV, 2023)

MVTrans: Multi-View Perception of Transparent Objects. - Yi Ru Wang; Yuchi Zhao; Haoping Xu; Sagi Eppel; Alán Aspuru-Guzik; Florian Shkurti; Animesh Garg (ICRA, 2023)

Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network. - Mario Krenn; Lorenzo Buffoni; Bruno C. Coutinho; Sagi Eppel; Jacob Gates Foster; Andrew Gritsevskiy; Harlin Lee; Yichao Lu; João P. Moutinho; Nima Sanjabi; Rishi Sonthalia; Ngoc Mai Tran; et al. (Nat. Mac. Intell., 2023)

Infusing Synthetic Data with Real-World Patterns for Zero-Shot Material State Segmentation. - Sagi Eppel; Jolina Li; Manuel S. Drehwald; Alán Aspuru-Guzik (NeurIPS, 2024)

Learning Zero-Shot Material States Segmentation, by Implanting Natural Image Patterns in Synthetic Data. - Sagi Eppel; Jolina Li; Manuel S. Drehwald; Alán Aspuru-Guzik (CoRR, 2024)

Vastextures: Vast repository of textures and PBR materials extracted from real-world images using unsupervised methods. - Sagi Eppel (CoRR, 2024)

Do large language vision models understand 3D shapes? - Sagi Eppel (CoRR, 2024)

Shape and Texture Recognition in Large Vision-Language Models. - Sagi Eppel; Mor Bismut; Alona Faktor (CoRR, 2025)