143 citations · 440 across the 42 of their papers we have counts for
6 papers · 1 filter
Program-Guided Image Manipulators
Jiayuan Mao, Xiuming Zhang, Yikai Li +3
Humans are capable of building holistic representations for images at various levels, from local objects, to pairwise relations, to global structures. The interpretation of structu…
Neurally-Guided Structure Inference
Sidi Lu, Jiayuan Mao, Joshua B. Tenenbaum +1
Most structure inference methods either rely on exhaustive search or are purely data-driven. Exhaustive search robustly infers the structure of arbitrarily complex data, but it is…
Visually Grounded Neural Syntax Acquisition
Haoyue Shi, Jiayuan Mao, Kevin Gimpel +1
We present the Visually Grounded Neural Syntax Learner (VG-NSL), an approach for learning syntactic representations and structures without any explicit supervision. The model learn…
UniVSE: Robust Visual Semantic Embeddings via Structured Semantic Representations
Hao Wu, Jiayuan Mao, Yufeng Zhang +4
We propose Unified Visual-Semantic Embeddings (UniVSE) for learning a joint space of visual and textual concepts. The space unifies the concepts at different levels, including obje…
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision
Jiayuan Mao, Chuang Gan, Pushmeet Kohli +2
We propose the Neuro-Symbolic Concept Learner (NS-CL), a model that learns visual concepts, words, and semantic parsing of sentences without explicit supervision on any of them; in…
Neural Logic Machines
Honghua Dong, Jiayuan Mao, Tian Lin +3
We propose the Neural Logic Machine (NLM), a neural-symbolic architecture for both inductive learning and logic reasoning. NLMs exploit the power of both neural networks---as funct…