Learning the Local Statistics of Optical Flow. - Dan Rosenbaum; Daniel Zoran; Yair Weiss (NIPS, 2013)

The Sample Complexity of Subspace Learning with Partial Information. - Alon Gonen; Dan Rosenbaum; Yonina C. Eldar; Shai Shalev-Shwartz (CoRR, 2014)

The Return of the Gating Network: Combining Generative Models and Discriminative Training in Natural Image Priors. - Dan Rosenbaum; Yair Weiss (NIPS, 2015)

Beyond Brightness Constancy: Learning Noise Models for Optical Flow. - Dan Rosenbaum; Yair Weiss (CoRR, 2016)

Statistics of RGBD Images. - Dan Rosenbaum; Yair Weiss (CoRR, 2016)

Subspace Learning with Partial Information. - Alon Gonen; Dan Rosenbaum; Yonina C. Eldar; Shai Shalev-Shwartz (J. Mach. Learn. Res., 2016)

Learning Generative Models and the Inference Process in Low Level Vision (שער נוסף בעברית: למידה של מודלים גנרטיביים ותהליך הסקה בראייה ראשונית.). - Dan Rosenbaum (2016)

Conditional Neural Processes. - Marta Garnelo; Dan Rosenbaum; Christopher Maddison; Tiago Ramalho; David Saxton; Murray Shanahan; Yee Whye Teh; Danilo Jimenez Rezende; S. M. Ali Eslami (ICML, 2018)

Neural Processes. - Marta Garnelo; Jonathan Schwarz; Dan Rosenbaum; Fabio Viola; Danilo J. Rezende; S. M. Ali Eslami; Yee Whye Teh (CoRR, 2018)

Learning models for visual 3D localization with implicit mapping. - Dan Rosenbaum; Frederic Besse; Fabio Viola; Danilo J. Rezende; S. M. Ali Eslami (CoRR, 2018)

Attentive Neural Processes. - Hyunjik Kim; Andriy Mnih; Jonathan Schwarz; Marta Garnelo; S. M. Ali Eslami; Dan Rosenbaum; Oriol Vinyals; Yee Whye Teh (ICLR (Poster), 2019)

Unsupervised Doodling and Painting with Improved SPIRAL. - John F. J. Mellor; Eunbyung Park; Yaroslav Ganin; Igor Babuschkin; Tejas Kulkarni; Dan Rosenbaum; Andy Ballard; Theophane Weber; Oriol Vinyals; S. M. Ali Eslami (CoRR, 2019)

A Neural Network Auction For Group Decision Making Over a Continuous Space. - Yoram Bachrach; Ian Gemp; Marta Garnelo; János Kramár; Tom Eccles; Dan Rosenbaum; Thore Graepel (IJCAI, 2021)

Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs. - Dan Rosenbaum; Marta Garnelo; Michal Zielinski; Charlie Beattie; Ellen Clancy; Andrea Huber; Pushmeet Kohli; Andrew W. Senior; John Jumper; Carl Doersch; S. M. Ali Eslami; Olaf Ronneberger; et al. (CoRR, 2021)

From data to functa: Your data point is a function and you can treat it like one. - Emilien Dupont; Hyunjik Kim; S. M. Ali Eslami; Danilo Jimenez Rezende; Dan Rosenbaum (ICML, 2022)

From data to functa: Your data point is a function and you should treat it like one. - Emilien Dupont; Hyunjik Kim; S. M. Ali Eslami; Danilo J. Rezende; Dan Rosenbaum (CoRR, 2022)

SeaThru-NeRF: Neural Radiance Fields in Scattering Media. - Deborah Levy; Amit Peleg; Naama Pearl; Dan Rosenbaum; Derya Akkaynak; Simon Korman; Tali Treibitz (CVPR, 2023)

Spatial Functa: Scaling Functa to ImageNet Classification and Generation. - Matthias Bauer 001; Emilien Dupont; Andy Brock; Dan Rosenbaum; Jonathan Schwarz; Hyunjik Kim (CoRR, 2023)

Osmosis: RGBD Diffusion Prior for Underwater Image Restoration. - Opher Bar Nathan; Deborah Levy; Tali Treibitz; Dan Rosenbaum (ECCV (62), 2024)

Robust Neural Processes for Noisy Data. - Chen Shapira; Dan Rosenbaum (CoRR, 2024)