Posted by on Dec 1, 2018 in events, news |

Talk of Wiktor Mlynarsky (IST, Vienna) on 18 December @ 1330

Inference and efficient coding in natural auditory scenes

Processing of natural stimuli in sensory systems has been traditionally studied within two theoretical frameworks: probabilistic inference and efficient coding. Probabilistic inference specifies optimal strategies for learning about relevant properties of the environment from local and ambiguous sensory signals. Efficient coding provides a normative approach to study encoding of natural stimuli in resource-constrained sensory systems. By emphasizing different aspects of information processing they provide complementary approaches to study sensory computations. Here, I will discuss applications of these two perspectives to study the problem of auditory scene analysis in natural environments. First, I will show that human auditory grouping can be understood as probabilistic inference constrained by natural sound statistics. Second, I will present a statistical model of natural sounds motivated by efficient coding principles. Through the talk I will discuss similarities and differences between these two approaches and conclude by proposing a unifying perspective on probabilistic inference and efficient coding in sensory systems