Modern Analysis(including Measure theory and Functional Analysis)
Harmonic Analysis(Fourier Analysis would suffice)
Abstract Algebra(including Galois Theory, reviewing Linear Algebra in algebraic perspective is one of the most important thing in Deep Learning)
General Topology
Probability theory in Graduate course
Statistical Inference
Bayesian Statistics
Numerical Optimization Techniques
Algorithms
Optional(Some kinda things prevalent in research society)
Stochastic process(GP and Bayesian approach in Deep Learning)
Differential Geometry and Manifolds
Harmonic Analysis(Fourier Analysis would suffice)
Abstract Algebra(including Galois Theory, reviewing Linear Algebra in algebraic perspective is one of the most important thing in Deep Learning)
General Topology
Probability theory in Graduate course
Statistical Inference
Bayesian Statistics
Numerical Optimization Techniques
Algorithms
Optional(Some kinda things prevalent in research society)
Stochastic process(GP and Bayesian approach in Deep Learning)
Differential Geometry and Manifolds
이분이 수갤 배우고싶다인가요?
아조씨 이스트는 어케됨; - dc App
요즘 논문 하나 쓰고 있오 그래서 아직 안넣음
님 저 올해 지원할 것 같은데 8월 전에좀 넣어서 붙어주셈;; 그래야 저 될 확률 올라감 - dc App
넹 노력해 볼게요 ㅠㅠ 저도 요즘 최선다하고 있음
괴수들끼리 붙냐 안붙냐 토론하네
카이스트는 랩 지원 끝났는데 - dc App
ㅋㅋㅋㅋㅋㅋ
time analysis ㅇㄷ?