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école centrale paris and a ms degree in mathematics vision and learning from ens paris saclay news 2026 we contributed an ai atmospheric model entry archesweathergen to the ai model intercomparison project aimip phase 1 a systematic evaluation framework for ai weather and climate models 2025 scivid cross domain evaluation of video models in scientific applications is accepted at iccv 2025 2025 century a framework and dataset for evaluating historical contextualisation of sensitive images is accepted at iclr 2025 2024 our paper scaling 4d representations is out on arxiv 2024 neural compression of atmospheric states which focuses on compression of weather and climate data is out on arxiv 2024 contributed to gemini a family of highly capable multimodal models 05 2022 first paper at deepmind on fewshot language and visual learning first authored by jean baptiste alayrac jeff donahue pauline luc and antoine miech accepted at neurips 2022 10 2022 new paper first authored by zerui chen accepted at eccv 2022 on hand object shape and pose estimation 11 2021 i joined deepmind as a research scientist 10 2021 i defended my phd thesis 08 2021 i am attending the 2021 cemracs summer program on data assimilation and reduced modeling for high dimensional problems in luminy 08 2021 outstanding reviewer for iccv 2021 08 2021 new paper on arxiv on joint hand object fitting to noisy evidence in short rgb clips 09 2020 i gave a talk to present our work on hand object reconstruction at the cs robotics reading group at the university of toronto 08 2020 we held the wicv workshop at eccv 20 08 2020 i completed a 3 month research internship at facebook ai research in paris 06 2020 cvpr 20 paper code released 06 2020 i completed a 6 month research internship at google 03 2020 cvpr 20 paper accepted code coming soon 10 2019 i presented at the mixed reality ai zurich lab workshop during my internship at microsoft 02 2019 cvpr 19 paper accepted on hand object reconstruction 09 2018 i coorganized the 5th wicv workshop which took place in conjunction with eccv 18 in munich 04 2018 i visited the perceiving systems team at mpi for a month 11 2017 i started my phd at willow 05 2017 i joined willow project team as a research intern research aimip phase 1 systematic evaluations of ai weather and climate models brian henn christopher s bretherton nikolay koldunov christian lessig maria j molina troy arcomano oliver watt meyer guillaume couairon renu singh robert brunstein yana hasson antonia jost noah brenowitz peter manshausen nathaniel cresswell clay dale durran kyle joseph chen hall janni yuval dmitrii kochkov stephan hoyer and ignacio lopez gomez arxiv preprint 2026 paper bibtex article henn2026aimip title aimip phase 1 systematic evaluations of ai weather and climate models author henn brian and bretherton christopher s and koldunov nikolay and lessig christian and molina maria j and arcomano troy and watt meyer oliver and couairon guillaume and singh renu and brunstein robert and hasson yana and jost antonia and brenowitz noah and manshausen peter and cresswell clay nathaniel and durran dale and hall kyle joseph chen and yuval janni and kochkov dmitrii and hoyer stephan and lopez gomez ignacio journal arxiv preprint arxiv 2605 06944 year 2026 abstract the ai weather and climate model intercomparison project aimip establishes a standardized framework for evaluating ai based weather and climate models phase 1 assesses participating models trained on era5 reanalysis data tasked with simulating the atmosphere from 1979 to 2024 models are evaluated across biases trends el niño responses temporal variability and out of sample generalization evaluating skill and stability of archesweather and archesweathergen under multi decadal climate simulations renu singh robert brunstein antonia jost thomas rackow claire monteleoni yana hasson christian lessig and guillaume couairon arxiv preprint 2026 paper bibtex article singh2026archesweather title evaluating skill and stability of archesweather and archesweathergen under multi decadal climate simulations author singh renu and brunstein robert and jost antonia and rackow thomas and monteleoni claire and hasson yana and lessig christian and couairon guillaume journal arxiv preprint arxiv 2605 29976 year 2026 abstract we evaluate archesweather deterministic and archesweathergen probabilistic flow matching when adapted for multi decadal climate simulation following the aimip phase 1 protocol despite their origins in short term weather forecasting both models produce stable long term climate simulations maintaining a stable annual cycle capturing climate variable drift and faithfully reproducing era5 climatology large scale circulations and interannual variability flamingo a visual language model for few shot learning neurips 2022 blogpost bibtex article alayrac2022flamingo title flamingo a visual language model for few shot learning author alayrac jean baptiste and donahue jeff and luc pauline and miech antoine and barr iain and hasson yana and lenc karel and mensch arthur and millican katie and reynolds malcolm and ring roman and rutherford eliza and cabi serkan and han tengda and gong zhitao and samangooei sina and monteiro marianne and menick jacob and borgeaud sebastian and brock andrew and nematzadeh aida and sharifzadeh sahand and binkowski mikolaj and barreira ricardo and vinyals oriol and zisserman andrew and simonyan karen journal arxiv preprint arxiv 2204 14198 year 2022 towards unconstrained joint hand object reconstruction from rgb videos yana hasson gül varol ivan laptev and cordelia schmid 3dv 2021 project page bibtex article hasson20_homan title nbsp nbsp nbsp nbsp towards unconstrained joint hand object reconstruction from rgb videos author nbsp nbsp hasson yana and varol g u l and laptev ivan and schmid cordelia journal nbsp arxiv preprint arxiv 2108 07044 year nbsp nbsp nbsp nbsp nbsp 2021 abstract our work aims to obtain 3d reconstruction of hands and manipulated objects from monocular videos reconstructing hand object manipulations holds a great potential for robotics and learning from human demonstrations the supervised learning approach to this problem however requires 3d supervision and remains limited to constrained laboratory settings and simulators for which 3d ground truth is available in this paper we first propose a learning free fitting approach for hand object reconstruction which can seamlessly handle two hand object interactions our method relies on cues obtained with common methods for object detection hand pose estimation and instance segmentation we quantitatively evaluate our approach and show that it can be applied to datasets with varying levels of difficulty for which training data is unavailable low bandwidth video chat compression using deep generative models maxime oquab pierre stock oran gafni daniel haziza tao xu peizhao zhang onur celebi yana hasson patrick labatut bobo bose kolanu thibault peyronnel camille couprie paper abstract to unlock video chat for hundreds of millions of people hindered by poor connectivity or unaffordable data costs we propose to authentically reconstruct faces on the receiver s device using facial landmarks extracted at the sender s side and transmitted over the network in this context we discuss and evaluate the benefits and disadvantages of several deep adversarial approaches in particular we explore quality and bandwidth trade offs for approaches based on static landmarks dynamic landmarks or segmentation maps we design a mobile compatible architecture based on the first order animation model of siarohin et al in addition we leverage spade blocks to refine results in important areas such as the eyes and lips we compress the networks down to about 3mb allowing models to run in real time on iphone 8 cpu this approach enables video calling at a few kbits per second an order of magnitude lower than currently available alternatives leveraging photometric consistency over time for sparsely supervised hand object reconstruction yana hasson bugra tekin federica bogo ivan laptev marc pollefeys and cordelia schmid cvpr 2020 project page bibtex inproceedings hasson20_handobjectconsist title nbsp nbsp nbsp nbsp leveraging photometric consistency over time for sparsely supervised hand object reconstruction author nbsp nbsp hasson yana and tekin bugra and bogo federica and laptev ivan and pollefeys marc and schmid cordelia booktitle cvpr year nbsp nbsp nbsp nbsp nbsp 2020 abstract modeling hand object manipulations is essential for understanding how humans interact with their environment while of practical importance estimating the pose of hands and objects during interactions is challenging due to the large mutual occlusions that occur during manipulation recent efforts have been directed towards fully supervised methods that require large amounts of labeled training samples collecting 3d ground truth data for hand object interactions however is costly tedious and error prone to overcome this challenge we present a method to leverage photometric consistency across time when annotations are only available for a sparse subset of frames in a video our model is trained end to end on color images to jointly reconstruct hands and objects in 3d by inferring their poses given our estimated reconstructions we differentiably render the optical flow between pairs of adjacent images and use it within the network to warp one frame to another we then apply a self supervised photometric loss that relies on the visual consistency between nearby images we achieve state of the art results on 3d hand object reconstruction benchmarks and demonstrate that our approach allows us to improve the pose estimation accuracy by leveraging information from neighboring frames in low data regimes learning joint reconstruction of hands and manipulated objects yana hasson gül varol dimitrios tzionas igor kalevatykh michael j black ivan laptev and cordelia schmid cvpr 2019 project page bibtex inproceedings hasson19_obman title nbsp nbsp nbsp nbsp learning joint reconstruction of hands and manipulated objects author nbsp nbsp hasson yana and varol g u l and tzionas dimitrios and kalevatykh igor and black michael j and laptev ivan and schmid cordelia booktitle cvpr year nbsp nbsp nbsp nbsp nbsp 2019 abstract estimating hand object manipulations is essential for interpreting and imitating human actions previous work has made significant progress towards reconstruction of hand poses and object shapes in isolation yet reconstructing hands and objects during manipulation is a more challenging task due to significant occlusions of both the hand and object while presenting challenges manipulations may also simplify the problem since the physics of contact restricts the space of valid hand object configurations for example during manipulation the hand and object should be in contact but not interpenetrate in this work we regularize the joint reconstruction of hands and objects with manipulation constraints we present an end to end learnable model that exploits a novel contact loss that favors physically plausible hand object constellations to train and evaluate the model we also propose a new large scale synthetic dataset obman with hand object manipulations our approach significantly improves grasp quality metrics over baselines on synthetic and real datasets using rgb images as input code geoarches star open source library for training running and evaluating ml models on geospatial weather and climate data manopth star port of mano differentiable hand as a pytorch differentiable layer kinetics_i3d_pytorch star port of i3d network for action recognition to pytorch transfer of weights trained on kinetics dataset torch_videovision star utilities for video data augmentation inflated_convnets_pytorch star inflation from image input to video inputs of resnets and densenets weights initialized based on imagenet useful computer vision phd resources star some useful tips and resources for phds in computer vision handobjectconsist star cvpr20 demo and training code for sparsely supervised hand object reconstruction with photometric supervision obman_train star cvpr19 demo evaluation and training code for hand object reconstruction obman star load the obman dataset obman_render star code to render the obman dataset homan star hand object joint fitting to noisy evidence miscellaneous podcasts i listen to acquired nvidia takeaway developping hardware in simulation skipping the prototyping step can work if you have a good simulator and don t care about one third of your functions crashing tiktok takeaway you can get really far from your starting point when trying to design an educational app whatsapp huberman lab research based advice to optimize your body and brain time perception entrainment by dopamine serotonin hormones how foods and nutrients control your mood takeaway i now supplement with omega3 understand improve memory using science based tools takeaway spike your adrenaline close to at the end or right after you are processing the information you want to retain apparently works with information you don t care about too what alcohol does to your body brain health tl dr stay significantly below 6 drinks a week to avoid numerous health drawbacks in french les balladeurs les mélodies du transsibérien sexplorer made by my sister sophie hasson les pieds sur terre deepfake attention au mirage amoureux passages des histoires avec plusieurs points de vues articles i enjoyed and or learned from 2022 a passage to parenthood by akhil sharma the new yorker 2021 half a billion in bitcoin lost in the dump by d t max the new yorker 2020 survivors guilt in the mountains by nick paumgarten the new yorker the underground movement trying to topple the north korean regime by suki kim the new yorker how venture capitalists are deforming capitalism by charles duhigg the new yorker rise and fall of wework i used to make fun of silicon valley preppers then i became one by nellie bowles the new york times 2019 the art of decision making by joshua rothman the new yorker the age of instagram face by jia tolentino the new yorker 2018 the white darkness by david grann the new yorker should we be worried about computerized facial recognition by david owen the new yorker 2017 the family that built an empire of pain by patrick radden keefe the new yorker and follow up the sackler family s plan to keep its billions 2012 the case against kids by elizabeth kolbert the new yorker altered states by oliver sachs the new yorker 1996 into thin air by jon krakauer outside magazine books science fiction short stories isaac asimov the complete stories by isaac asimov in particular profession the fun they had and franchise axiomatic by greg egan in particular learning to be me and closer non fiction the man who mistook his wife for a hat and other clinical tales by oliver sacks when breath becomes air by paul kalanithi the snow leopard by ...