no code implementations • 24 Apr 2024 • Vaisakh Shaj
Machines that can replicate human intelligence with type 2 reasoning capabilities should be able to reason at multiple levels of spatio-temporal abstractions and scales using internal world models.
1 code implementation • NeurIPS 2023 • Vaisakh Shaj, Saleh Gholam Zadeh, Ozan Demir, Luiz Ricardo Douat, Gerhard Neumann
Intelligent agents use internal world models to reason and make predictions about different courses of their actions at many scales.
1 code implementation • ICLR 2022 • Vaisakh Shaj, Dieter Buchler, Rohit Sonker, Philipp Becker, Gerhard Neumann
Recurrent State-space models (RSSMs) are highly expressive models for learning patterns in time series data and system identification.
no code implementations • 27 May 2022 • Moritz Reuss, Niels van Duijkeren, Robert Krug, Philipp Becker, Vaisakh Shaj, Gerhard Neumann
These models need to precisely capture the robot dynamics, which consist of well-understood components, e. g., rigid body dynamics, and effects that remain challenging to capture, e. g., stick-slip friction and mechanical flexibilities.
2 code implementations • 20 Oct 2020 • Vaisakh Shaj, Philipp Becker, Dieter Buchler, Harit Pandya, Niels van Duijkeren, C. James Taylor, Marc Hanheide, Gerhard Neumann
We adopt a recent probabilistic recurrent neural network architecture, called Re-current Kalman Networks (RKNs), to model learning by conditioning its transition dynamics on the control actions.
no code implementations • 27 Apr 2020 • Konda Reddy Mopuri, Vaisakh Shaj, R. Venkatesh Babu
Therefore, the metric to quantify the vulnerability of the models should capture the severity of the flipping as well.
1 code implementation • 20 May 2019 • Gaurav Kumar Nayak, Konda Reddy Mopuri, Vaisakh Shaj, R. Venkatesh Babu, Anirban Chakraborty
Without even using any meta-data, we synthesize the Data Impressions from the complex Teacher model and utilize these as surrogates for the original training data samples to transfer its learning to Student via knowledge distillation.
no code implementations • 2 Dec 2017 • Vaisakh Shaj, Puranjoy Bhattacharya
Audio events are quite often overlapping in nature, and more prone to noise than visual signals.