Janis Postels
@JanisPostels
Will be presenting our work "On the Practicality of Deterministic Epistemic Uncertainty" next week at #ICML2022 in Baltimore. If you are interested checkout our paper or visit us at our poster on Tue Jul 19 between 06:30 PM & 08:30 PM @ Hall E 506 arxiv.org/abs/2107.00649
I am excited to share that our work "3D Compositional Zero-shot Learning with DeCompositional Consensus" has been accepted at #ECCV2022. Joint work with @evinpinar @xyongqin, Luc Van Gool and @fedassa between ETH Zurich, TUM, and Google. arxiv.org/abs/2111.14673 [1/7]
Looking forward to this :)
Jakob Heiss will present his ICML paper "NOMU - Neural Optimization-based Model Uncertainty" at the Uncertainty in AI reading group today at 5:30pm (Berlin time). uncertainty-reading-group.github.io/2021-11-28-tal… Co-author: @JWeissteiner, Hanna Wutte, @SvenSeuken, Josef Teichmann
Will be presenting our work "ManiFlow: Implicitly Representing Manifolds with Normalizing Flows" at #3DV tomorrow! We show how to sample from manifolds (e.g. Point Clouds) with normalizing flows! @MDanelljan Luv Van Gool @fedassa Paper: arxiv.org/abs/2208.08932
If your are at #ICML2022, join us Thursday at 11:00 in the Ballroom 1&2 for our oral presentation on "Overcoming Oscillations in Quantization-Aware Training" and later at poster #227. Paper: arxiv.org/abs/2203.11086 @mfournarakis, @yell1337, @TiRune.
Would you rather play games or watch random images? In our #ICML2022 work, we give RL agents this choice and turns out many curiosity algos would prefer to watch random images. We propose an acetylcholine-inspired solution to help curiosity to avoid these "noisy TVs"
The MobileCodec paper is now online: arxiv.org/abs/2207.08338 Check it out if you want to know how we were able to deploy a neural video codec to a mobile phone and decode 720p video in real time 📲
Great work guys!
@CVPR time has finally come! Check out our paper "SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation" and drop by our poster session on Friday 24 (afternoon) at 257B to learn more! Project Page: vis.xyz/shift/ Paper: go.yf.io/shift-paper
Cool new AD dataset in town 👉 SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation by @JanisPostels @MattiaSegu @DrFisherYu @fedassa et al. vis.xyz/shift/ 1/
Our work on Variational Transformer Networks for layout generation got featured on the Google AI blog. The work will be presented at CVPR21 on June 24th and a pre-release is available on arXiv. Blog post: Official Tweet: https:/…lnkd.in/dSuZVFx lnkd.in/dBgXeRp
Quantifying Aleatoric and Epistemic Uncertainty Using Density Estimation in Latent Space. arxiv.org/abs/2012.03082
Looking forward to interesting discussions :-)
Our poster on uncertainty estimation for neural networks presented today at the NeurIPS Bayesian DL meetup (poster F13) arxiv.org/abs/2012.03082 bayesiandeeplearning.org
Very happy to share that 5 of our papers got accepted at #eccv2020, of which 3 as orals (top 2% this year). Kudos to all my awesome co-authors across Google, TUM, Stanford, Oxford, Chalmers, Tsinghua (among others) for the great work and results. More det…lnkd.in/dZDq8AM