40 citations · 107 across the 6 of their papers we have counts for
7 papers
Adaptive Uncertainty-Guided Model Selection for Data-Driven PDE Discovery
Pongpisit Thanasutives, Takashi Morita, Masayuki Numao +1
We propose a new parameter-adaptive uncertainty-penalized Bayesian information criterion (UBIC) to prioritize the parsimonious partial differential equation (PDE) that sufficiently…
Noise-aware Physics-informed Machine Learning for Robust PDE Discovery
Pongpisit Thanasutives, Takashi Morita, Masayuki Numao +1
This work is concerned with discovering the governing partial differential equation (PDE) of a physical system. Existing methods have demonstrated the PDE identification from finit…
Exploring TTS without T Using Biologically/Psychologically Motivated Neural Network Modules (ZeroSpeech 2020)
Takashi Morita, Hiroki Koda
In this study, we reported our exploration of Text-To-Speech without Text (TTS without T) in the Zero Resource Speech Challenge 2020, in which participants proposed an end-to-end,…
Neural Language Models as Psycholinguistic Subjects: Representations of Syntactic State
Richard Futrell, Ethan Wilcox, Takashi Morita +3
We deploy the methods of controlled psycholinguistic experimentation to shed light on the extent to which the behavior of neural network language models reflects incremental repres…
Superregular grammars do not provide additional explanatory power but allow for a compact analysis of animal song
Takashi Morita, Hiroki Koda
A pervasive belief with regard to the differences between human language and animal vocal sequences (song) is that they belong to different classes of computational complexity, wit…
RNNs as psycholinguistic subjects: Syntactic state and grammatical dependency
Richard Futrell, Ethan Wilcox, Takashi Morita +1
Recurrent neural networks (RNNs) are the state of the art in sequence modeling for natural language. However, it remains poorly understood what grammatical characteristics of natur…
What do RNN Language Models Learn about Filler-Gap Dependencies?
Ethan Wilcox, Roger Levy, Takashi Morita +1
RNN language models have achieved state-of-the-art perplexity results and have proven useful in a suite of NLP tasks, but it is as yet unclear what syntactic generalizations they l…