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Hi there 👋

I'm a late stage PhD student at the Max Planck International Research School for Intelligent Systems, Univerity of Tübingen, and University of Göttingen. Since 2019, I'm part of the Neuronal Intelligence Team, led by Fabian Sinz. I work in collaboration with Andreas Tolias, Alexander Ecker, Katrin Franke, and Ziad Hafed.

I'm fascinated in equal parts by Neuroscience, especially the visual system, and Machine Learning. Seeing how AI can help with fundamental scientific discoveries is remarkable. I'm happy to be there for the ride, and to contribute where I can. Looking forward to how Neuroscience and ML might co-develop.

In current projects, I'm building neural predictive models on the basis of CNNs to predict neuronal activity in mouse and monkey. I'm also interested in how neural data can be used to make CNNs more robust to common image distortions. I'm the lead organizer (jointly with Paul Fahey from the Baylor College of Medicine) of the SENSORIUM competition - a multi lab effort to find the best neural predictive model of mouse V1, and at the same time making our neural predictive models accessible. I'm the happiest when I can create visualizations and to tinker with the latest tools to help with data analysis.

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Konstantin Willeke's Projects

cornet icon cornet

[NeurIPS'19 Oral] CORnet: Modeling the Neural Mechanisms of Core Object Recognition

fitgabor icon fitgabor

A simple tool to find the Gabor filter that maximizes the output of your neuron model

generativeimagemodellingwithdnns icon generativeimagemodellingwithdnns

Here I will share the code from the lectures of the course: Generative Image Modelling with Deep Neural Networks taught in the Summer Term 2017 at the Graduate School for Neural Information Processing, University of Tuebingen.

lipstick icon lipstick

Collection of simple-to-use methods to make visualization more convenient

lucent icon lucent

Lucid library adapted for PyTorch

mei icon mei

Visualize features cells are responsive to via gradient ascent.

multimodal icon multimodal

TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.

nndichromacy icon nndichromacy

Project reposity for mouse color MEIs, in collaboration with Katrin Franke and the BCM.

nnfabrik icon nnfabrik

A generalized model fitting pipeline that houses models, trainers, and datasets in datajoint and returns as well as stores trained models.

nnvision icon nnvision

Envisioning the biological visual system with deep neural networks.

pysaliency icon pysaliency

Python Framework for Saliency Modeling and Evaluation

pytorch icon pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

sinz2018_nips icon sinz2018_nips

Code for the NIPS 2018 paper: "Stimulus domain transfer in recurrent models for large scale cortical population prediction on video"

t-simcne icon t-simcne

Unsupervised visualization of image datasets using contrastive learning

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