Multi-Entity Dependence Learning with Rich Context via Conditional Variational Auto-encoder

Multi-Entity Dependence Learning (MEDL) explores conditional correlations among multiple entities. The availability of rich contextual information requires a nimble learning scheme that tightly integrates with deep neural networks and has the ability to capture correlation structures among exponentially many outcomes. We propose MEDL_CVAE, which encodes a conditional multivariate distribution as a generating process. As a result, the variational lower bound of the joint likelihood can be optimized via a conditional variational auto-encoder and trained end-to-end on GPUs. Our MEDL_CVAE was motivated by two real-world applications in computational sustainability: one studies the spatial correlation among multiple bird species using the eBird data and the other models multi-dimensional landscape composition and human footprint in the Amazon rainforest with satellite images. We show that MEDL_CVAE captures rich dependency structures, scales better than previous methods, and further improves on the joint likelihood taking advantage of very large datasets that are beyond the capacity of previous methods.Comment: The first two authors contribute equall

Large energy soliton erbium-doped fiber laser with a graphene-polymer composite mode locker

Due to its unique electronic property and the Pauli Blocking Principle, atomic layer graphene possesses wavelength-independent ultrafast saturable absorption, which can be exploited for the ultrafast photonics application. Through chemical functionalization, a graphene-polymer nanocomposite membrane was fabricated and firstly used to mode lock a fiber laser. Stable mode locked solitons with 3 nJ pulse energy, 700 fs pulse width at the 1590 nm wavelength have been directly generated from the laser. We show that graphene-polymer nanocomposites could be an attractive saturable absorber for high power fiber laser mode locking.Comment: Large energy soliton erbium-doped fiber laser with a graphene-polymer composite mode locker. Applied Physics Letters, Accepte

Graphene mode locked, wavelength-tunable, dissipative soliton fiber laser

Atomic layer graphene possesses wavelength-insensitive ultrafast saturable absorption, which can be exploited as a full-band mode locker. Taking advantage of the wide band saturable absorption of the graphene, we demonstrate experimentally that wide range (1570 nm - 1600nm) continuous wavelength tunable dissipative solitons could be formed in an erbium doped fiber laser mode locked with few layer graphene