March 2023
Abstract: The recent success in Computer Vision has been mostly attributed to improved results using deep learning models trained on large labeled datasets. Many of these datasets have been labeled by humans. The labeling process, however, can be time-consuming, and in many applications, it may require expertise that could be costly to acquire. In order to…
Abstract: In this talk, Dr. Jung will focus on the three key principles of good time management: defining priorities, managing expectations and developing routines that work. Following the lecture, the participants have the opportunity to discuss their time management challenges in an individual coaching session. Defining Priorities: Dealing with high performance expectations in wide array of…
Abstract: The classic view of nature is one of a deathly struggle for existence. Yet, throughout nature, organisms cooperate with each other. Mutualisms – mutually beneficial interactions between species - are more than fascinating natural history stories: they are central to the diversity and the diversification of life on Earth. Charles Darwin, well aware of mutualisms,…
February 2023
Abstract: The capabilities of AI systems are improving rapidly, and these systems are being deployed in increasingly complex and high-stakes contexts, from self-driving cars to the detection of medical conditions. As the importance of AI grows, so too does the need for robust evaluation. If we want to determine the extent to which systems are safe,…
Abstract: This talk will be targeting junior postdocs and phd at their final stages. It will be a short and brief introduction to the major options for grants (those aiming at the stars or smaller ones). Julten will offer some quick tips on the application process. She will also share her own experience in applying to…
Abstract: Biological intelligent systems manifest their intelligence in physical interactions with other agents and with their environment. Such interactions require embodiment. Intelligence, both artificial and biological, also requires some kind of learning. But what is the relationship between the two? How should the two interact? Do they even have to? What could be a common ground…
Abstract: I investigate how large groups of simple robots can reach a consensus with decentralized minimalistic algorithms. Simple robots can be useful in nanorobotics and in scenarios with low-cost requirements. I show that through decentralized voting algorithms, swarms of minimalistic robots can make best-of-n decisions. In my research, I show that using a biologically-inspired voting model…
January 2023
Lars Lewejohann, Freie Universität Berlin, German Federal Institute for Risk Assessment (BfR), German Centre for the Protection of Laboratory Animals (Bf3R) Mice, like all other living creatures, have adapted to specific living conditions in the course of evolution. From a human point of view, the behavior of animals is therefore not always easy to understand. This…
Abstract: From writing essays to evaluating potential hires, machines are doing a lot these days. In all spheres of life, it seems that machines are being delegated more and more decisions. Some of these machines are being delegated decisions that could have significant impact on human lives.Examples of such machines which have caused such impact are…
Abstract: Unsupervised learning is experiencing a renaissance. Driven by an abundance of unlabelled data and the advent of deep generative models, machines are now able to synthesise complex images, videos and sounds. In robotics, one of the most promising features of these models - the ability to learn structured latent spaces - is gradually gaining traction.…
Abstract: Swarm robotics is a promising approach to the coordination of large groups of robots. Traditionally, the design of collective behaviors for robot swarms has been an iterative manual process: a human designer manually refines the control software of the individual robots until the desired collective behavior emerges. In this talk, I discuss automatic design as…
Abstract: In groups of agents learning how to solve a common task, interaction and knowledge transfer between agents is important and can vary depending on network topology. Heterogeneity is one of the key principles that influences the type and quality of interaction between learning agents. Different learning strategies and behaviors can be a driving factor for…
Abstract: We can view cortex from two fundamentally different perspectives: a powerful device for performing optimal inference, or an assembly of biological components not built for achieving statistical optimality. The former approach is attractive thanks to its elegance and potentially wide applicability, however the basic facts of human pattern vision do not support it. Instead, they…
Abstract: Teleosts engage in diverse social activities, ranging from the highly gregarious zebrafish to the solitary Siamese fighting fish. When presented with conspecifics, these social tendencies produce stereotyped behaviours: zebrafish shoal towards their conspecifics, while fighting fish engage in aggressive displays. Under certain conditions, these behavioural patterns are sufficiently robust to support visual psychophysics and demonstrate…
December 2022
Many claims have been made that machine intelligence could make humans superfluous in the near future. Today this claim is largely seen as overstated, but it is still important to assess the relative strengths of human versus machine cognition. ***Want to attend one of our events? Sign up here. To get regular updates, subscribe…