Amyotrophic lateral sclerosis is a fatal disease that not only affects
m...
Scientific Machine Learning (SciML) is a burgeoning field that
synergist...
Recent advances in large language models (LLMs) have led to the developm...
We introduce a Reinforcement Learning Psychotherapy AI Companion that
ge...
We present the TherapyView, a demonstration system to help therapists
vi...
The technical capacity to monitor patients with a mobile device has
dras...
As a predictive measure of the treatment outcome in psychotherapy, the
w...
Chronic pain is a pervasive disorder which is often very disabling and i...
In this work, we compare different neural topic modeling methods in lear...
The therapeutic working alliance is an important predictor of the outcom...
Unlike traditional time series, the action sequences of human decision m...
Prisoner's Dilemma mainly treat the choice to cooperate or defect as an
...
Artificial behavioral agents are often evaluated based on their consiste...
Recently, kernelized locality sensitive hashcodes have been successfully...
Drawing an inspiration from behavioral studies of human decision making,...
Drawing an inspiration from behavioral studies of human decision making,...
Many real-world data sets, especially in biology, are produced by highly...
We propose a novel machine-learning framework for dialogue modeling whic...
We consider an extension of the contextual bandit setting, motivated by
...
Kernel similarity functions have been successfully applied in classifica...
In this paper we propose an efficient algorithm ProtoDash for selecting
...
In this paper, we focus on online representation learning in non-station...
This workshop explores the interface between cognitive neuroscience and
...
Discourse varies with age, education, psychiatric state and historical e...
The massive availability of digital repositories of human thought opens
...