Power Spectral Density Reconstruction I am from an ML background and I am working on MP3 audio reconstruction and I have managed some amount of spectrogram reconstruction but I have noticed that the higher frequency end of the generated Power Spectral Density plot(Wave2) isn't matching with the original audio's plot (Wave1).

There is a similar distribution in the magnitude spectrum which is obvious since the two are linked. I wanted to know if there is any way I could regenerate the higher frequency power (or magnitude) because I cannot map the input PSD data to output PSD data as there is no way to convert the PSD data back to an audio clip even if I am successful in mapping them. The real and imaginary part re-constructions for the spectrogram reconstruction are visually pretty accurate but I am still unsure about how to approach this issue. Any guidance would be great!
A few observations

Your pictures looks odd. &quot;Wave 1&quot; doesn't look like an original audio file but something that has already been encoded/decoded and aggressively lowpass filtered in the process. Your reconstructed audio (Wave 2) actually as MORE high frequency energy, which I suspect is simply just quantization noise from the other bands. The expected spectrum of music is roughly pink (3dB/octave) up to about 10 kHz and then a steeper decline (maybe 10dB octave) to 20 kHz and above. There shouldn't be a step function in the spectrum.
The standard method of recovering for lost high frequency spectrum is Spectral Replication. That's been already implemented in some of the more modern codec standards (e.g. AAC) although not in MP3. See for example http://www.stockis.se/AES112th_SBR.pdf
If you want to do any commercial work in this area, I highly recommend studying the patent situation carefully.  A massive amount of work has already been done in this field and since the license revenue is quite substantial, the work has been well protected by patents and there is incentive to enforce them.