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Mengmi Zhang (Harvard Medical School), “A peek into how brain computations inspire new paths in AI and how AI elucidate brain computations”

On Zoom

Abstract: The fields of neuroscience and AI have a long and intertwined history. From the study of simple and complex cells in visual areas of the brain to the recent success of convolution neural networks in many real-world applications, experimental and theoretical neuroscience has contributed significantly to designing smarter machines. In turn, AI models help us better understand

PI Lecture

Henning Sprekeler (Science of Intelligence), “Harnessing machine learning to model biological systems”

"Harnessing machine learning to model biological systems" Abstract: Classically, models of biological systems follow two different approaches. In bottom-up approaches, biological data are used to constrain a phenomenological model of the system in question, and the model is the studied to identify potential functions or potential consequences of the observations that flow into the model.

Thursday Morning Talk

Mathilde Caron, “Self-Supervised Learning: How to learn from images without human annotations”

On Zoom

Abstract: Self-supervised learning (SSL) consists in training neural network systems without using any human annotations. Typically, neural networks require large amounts of annotated data, which have limited their applications in fields where accessing these annotations is expensive or difficult. Moreover, manual annotations are biased towards a specific task and towards the annotator's own biases, which

Thursday Morning Talk

Yuejiang Liu (EPFL University), “Learning Beyond the IID Setting with Robust and Adaptive Representations”

On Zoom

Abstract Machine learning models have achieved stunning successes in the IID setting. Yet, beyond this setting, existing models still suffer from two grand challenges: brittle under covariate shift and inefficient for knowledge transfer. In this talk, I will introduce three approaches to tackle these challenges, namely self-supervised learning, causal representation learning, and test-time training. More

PI Lecture

Marcel Brass (Science of Intelligence), “The cognitive neuroscience of implementing novel instructions”

One fundamental difference between human and non-human animals is the ability of humans to instantaneously implement instructed behaviour. While other animals acquire new behaviour via effortful trial-and-error learning or extensive practice, humans can implement novel behaviour based on instructions. This ability is presumably a key aspect of cultural learning. In my talk, I will discuss

Thursday Morning Talk

Chaz Firestone (Johns Hopkins University), “Seeing ‘How'”

On Zoom

Abstract: What is perception? The most intuitive and influential answer to this question has long been the one given by David Marr: To see the world is “to know what is where by looking” - to transform light into representations of objects and their features, located somewhere ins pace. But is this all that perception

Thursday Morning Talk

Mark Nawrot (North Dakota University), “Pursuit eye movements in the perception of depth from motion parallax”

On Zoom

Abstract: The brain performs critical calculations on visual information as we swiftly, yet effortlessly, navigate around objects and obstacles in our cluttered environment. Perhaps one of the most important calculations is for the perception of depth using the apparent relative motion of objects in the environment created by our own translation known as motion parallax.

Thursday Morning Talk

Henning Sprekeler (Science of Intelligence), “Architectural Design Principles for Intelligence: Modularity vs. Integration”

On Zoom

Abstract: The world is modular. So – intuitively – it seems clear that cognitive systems that deal with the world should benefit from a modular architecture. Simple or less important problems should use less cognitive resources than complex or important problems, which – intuitively – may be achieved by changing the degree of modularity that

Thursday Morning Talk

Global Scientific Exchange Program – Part I

On Zoom

The talks will be held by Arinze Lawrence Folarin, "My 175 days journey in Berlin"; Juliana T.C. Marcos "GSEP Internship: More than a research experience in neuromorphic vision at SCIoI"; and Kiprono Elijah Koech "Action Recognition in a Wildlife Setting - Taken a Leap". The Zoom Link will be sent the day before the lecture.

Thursday Morning Talk

Global Scientific Exchange Program – Part II

On Zoom

The talks will be held by Emmanuel Ousu Ahenkan and Tatiana Ngoli Moteu Marcos. The Zoom Link will be sent the day before the lecture.

Thursday Morning Talk

Earlybird UNI-X

On Zoom

Meet Philipp Semmer and Frederic du Bois-Reymond, both partners at the venture capital firm Earlybird UNI-X. They will talk about funding for university spin-offs and why they believe that scientist and researcher should be more excited about entrepreneurship. They will also share their insights on deep tech companies becoming the next generation of unicorns. The