1 code implementation • 27 Oct 2023 • Han Huang, Fernanda De La Torre, Cathy Mengying Fang, Andrzej Banburski-Fahey, Judith Amores, Jaron Lanier
We introduce a novel method for real-time animation control and generation on rigged models using natural language input.
no code implementations • 21 Sep 2023 • Fernanda De La Torre, Cathy Mengying Fang, Han Huang, Andrzej Banburski-Fahey, Judith Amores Fernandez, Jaron Lanier
We present Large Language Model for Mixed Reality (LLMR), a framework for the real-time creation and modification of interactive Mixed Reality experiences using LLMs.
no code implementations • 7 Jun 2023 • Jaesung Yoo, Fernanda De La Torre, Guangyu Robert Yang
In such dual-policy agents, a model-free policy and a distilled policy are used for model-free actions and planned actions, respectively.
no code implementations • 21 Jul 2021 • Andrzej Banburski, Fernanda De La Torre, Nishka Pant, Ishana Shastri, Tomaso Poggio
Recent theoretical results show that gradient descent on deep neural networks under exponential loss functions locally maximizes classification margin, which is equivalent to minimizing the norm of the weight matrices under margin constraints.
no code implementations • 12 Mar 2019 • Andrzej Banburski, Qianli Liao, Brando Miranda, Lorenzo Rosasco, Fernanda De La Torre, Jack Hidary, Tomaso Poggio
In particular, gradient descent induces a dynamics of the normalized weights which converge for $t \to \infty$ to an equilibrium which corresponds to a minimum norm (or maximum margin) solution.