--- title: "Danilo Jimenez Rezende — author profile and papers in our library" description: "Danilo Jimenez Rezende, Google DeepMind: 3 papers on Elamur Research (2014–2015), h-index 36 — affiliations, topics, co-authors and…" canonical: "https://research.elamur.ai/free/en/authors/danilo-jimenez-rezende/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/danilo-jimenez-rezende/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Danilo Jimenez Rezende # Danilo Jimenez Rezende Danilo Jimenez Rezende has 3 papers in our library, in 2014–2015, most of them on [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/); often with [Daan Wierstra](https://md.research.elamur.ai/free/en/authors/daan-wierstra/), [Shakir Mohamed](https://md.research.elamur.ai/free/en/authors/shakir-mohamed/), [Alex Graves](https://md.research.elamur.ai/free/en/authors/alex-graves/). 3 papers in our library · 2014–2015 [OpenAlex](https://openalex.org/A5055733526) · [ORCID](https://orcid.org/0000-0003-3184-8509) · [Wikidata](https://www.wikidata.org/wiki/Q69410236) · [**h-index 36**](https://openalex.org/authors/A5055733526) · [93 works](https://openalex.org/works?filter=author.id:A5055733526) · [11,568 citations](https://openalex.org/works?filter=author.id:A5055733526&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/danilo-jimenez-rezende/#papers) · [🔗 Cited 994 times in our library](https://md.research.elamur.ai/free/en/authors/danilo-jimenez-rezende/cited-by/) · [10 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #681](https://md.research.elamur.ai/free/en/paper-stars/page/7/#star-681) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Danilo+Jimenez+Rezende) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Danilo+Jimenez+Rezende) · [dblp](https://dblp.org/search?q=Danilo+Jimenez+Rezende) · [ACL Anthology](https://aclanthology.org/search/?q=Danilo+Jimenez+Rezende) ## Affiliations [🏢**Google DeepMind** London · United Kingdom 2012–2024 · 34 papersEmployment since 2014*current*](https://md.research.elamur.ai/free/en/companies/google-deepmind/) · [🏢**Google** Mountain View · United States 2015–2020 · 21 papers](https://md.research.elamur.ai/free/en/companies/google/) · [🔬**Centre de Physique Théorique** Marseille · France 2008–2009 · 3 papers](https://ror.org/052bbtn31) · [🏢**Google** London · United Kingdom 2016–2023 · 2 papers](https://md.research.elamur.ai/free/en/companies/google-united-kingdom/) · [🎓**Massachusetts Institute of Technology** Cambridge · United States 2022–2023 · 2 papers](https://md.research.elamur.ai/free/en/universities/massachusetts-institute-of-technology/) · [🎓**École Polytechnique Fédérale de Lausanne** Lausanne · Switzerland 2011–2014 · 2 papersEducation until 2013](https://md.research.elamur.ai/free/en/universities/ecole-polytechnique-federale-de-lausanne/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 7 more institutions on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 5 The field of science this work belongs to (OpenAlex fields).[Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Mathematics · 2 works](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [Statistics and Probability · 2 works](https://md.research.elamur.ai/free/en/shelves/mathematics/statistics-and-probability/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) 🧭 Topics 1 Research subjects and languages the work is about.[Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) ## Works by year ### 2010s [**2015** 2 papers](https://md.research.elamur.ai/free/en/authors/danilo-jimenez-rezende/year/2015/) · [**2014** 1 paper](https://md.research.elamur.ai/free/en/authors/danilo-jimenez-rezende/year/2014/) ## Papers The most cited first (OpenAlex and our library). 1. **[Stochastic Backpropagation and Approximate Inference in Deep Generative Models](https://md.research.elamur.ai/free/en/papers/rezende-2014-stochastic-backpropagation-approximate-inference-deep/)** *(2014 · 2,765 citations)* The paper addresses a long-standing difficulty with deep directed generative models: sampling from them is easy, but inferring their hidden variables efficiently has been hard. 2. **[Variational Inference with Normalizing Flows](https://md.research.elamur.ai/free/en/papers/rezende-2015-variational-inference-normalizing-flows/)** *(2015 · 1,441 citations)* Variational inference usually relies on simple posterior families, such as mean-field or diagonal Gaussians, so the approximation can never match the true posterior. 3. **[DRAW: A Recurrent Neural Network For Image Generation](https://md.research.elamur.ai/free/en/papers/gregor-2015-draw-recurrent-neural-network-image/)** *(2015 · 947 citations)* Most neural generative models of images produce the whole picture in one step from a single latent code. This makes self-correction impossible and scales poorly to large images. DRAW (Deep Recurrent Attentive Writer), from Google DeepMind, instead builds an image gradually, much as a person sketches and then refines.… ## All works 13 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them. 1. [**Stochastic Backpropagation and Approximate Inference in Deep Generative Models arXiv:1401.4082**Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra*2014 · 2,765 citations*](https://md.research.elamur.ai/free/en/papers/rezende-2014-stochastic-backpropagation-approximate-inference-deep/) 2. **[Semi-Supervised Learning with Deep Generative Models ↗](https://arxiv.org/abs/1406.5298) UvA-DARE (University of Amsterdam) · no summary yet**Diederik P. Kingma et al.*2014 · 1,550 citations* 3. [**Variational Inference with Normalizing Flows**Danilo Jimenez Rezende, Shakir Mohamed*2015 · 1,441 citations*](https://md.research.elamur.ai/free/en/papers/rezende-2015-variational-inference-normalizing-flows/) 4. [**DRAW: A Recurrent Neural Network For Image Generation arXiv:1502.04623**Karol Gregor, Ivo Danihelka, Alex Graves, et al.*2015 · 947 citations*](https://md.research.elamur.ai/free/en/papers/gregor-2015-draw-recurrent-neural-network-image/) 5. **[Interaction Networks for Learning about Objects, Relations and Physics ↗](https://arxiv.org/abs/1612.00222) arXiv:1612.00222 · no summary yet**Peter W. Battaglia et al.*2016 · 581 citations* 6. **[Neural scene representation and rendering ↗](https://doi.org/10.1126/science.aar6170) Science · no summary yet**S. M. Ali Eslami et al.*2018 · 518 citations* 7. **[Imagination-Augmented Agents for Deep Reinforcement Learning ↗](https://arxiv.org/abs/1707.06203) arXiv (Cornell University) · no summary yet**Théophane Weber et al.*2017 · 241 citations* 8. **[Unsupervised Predictive Memory in a Goal-Directed Agent ↗](https://arxiv.org/abs/1803.10760) arXiv (Cornell University) · no summary yet**Greg Wayne et al.*2018 · 140 citations* 9. **[Towards Conceptual Compression ↗](https://openalex.org/W2963147844) neural information processing systems · no summary yet**Karol Gregor et al.*2016 · 118 citations* 10. **[Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving ↗](https://arxiv.org/abs/2405.12205) arXiv:2405.12205 · no summary yet**Aniket Didolkar et al.*2024 · 45 citations* 11. **[Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions ↗](https://arxiv.org/abs/1710.10304) arXiv (Cornell University) · no summary yet**Scott Reed et al.*2017 · 43 citations* 12. **[A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities ↗](https://arxiv.org/abs/1905.13077) arXiv (Cornell University) · no summary yet**Simon Köhl et al.*2019 · 23 citations* 13. **[Towards Principled Unsupervised Learning ↗](https://arxiv.org/abs/1511.06440) arXiv (Cornell University) · no summary yet**Ilya Sutskever et al.*2015 · 21 citations* ## Co-authors here 3 co-authors with a page, the most papers together first. - [Daan Wierstra](https://md.research.elamur.ai/free/en/authors/daan-wierstra/) ×2 - [Shakir Mohamed](https://md.research.elamur.ai/free/en/authors/shakir-mohamed/) ×2 - [Alex Graves](https://md.research.elamur.ai/free/en/authors/alex-graves/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - Science - UvA-DARE (University of Amsterdam) - neural information processing systems ## Cited by Papers of our library cite their works 994 times (of the 149,439 papers whose bibliographies we read); [73 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/danilo-jimenez-rezende/cited-by/). Updated 2 November 2026